Methods For Rapid Forensic Analysis Of Mitochondrial DNA And Characterization Of Mitochondrial DNA Heteroplasmy

ABSTRACT

The present invention provides methods for rapid forensic analysis of mitochondrial DNA and methods for characterizing heteroplasmy of mitochondrial DNA, which can be used to assess the progression of mitochondrial diseases.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. application Ser. No.10/323,438 filed Dec. 18, 2002, which is incorporated herein byreference in its entirety. This application is also acontinuation-in-part of U.S. application Ser. No. 09/798,007 filed Mar.2, 2001, which is incorporated herein by reference in its entirety. Thisapplication also claims priority to U.S. provisional application Ser.No. 60/431,319 filed Dec. 6, 2002, which is incorporated herein byreference in its entirety.

FIELD OF THE INVENTION

This invention relates to the field of mitochondrial DNA analysis. Theinvention enables the rapid and accurate identification of individualsand eukaryotic organisms by forensics methods as well ascharacterization of mitochondrial DNA heteroplasmy and prediction ofonset of mitochondrial diseases.

BACKGROUND OF THE INVENTION

Mitochondrial DNA (mtDNA) is found in eukaryotes and differs fromnuclear DNA in its location, its sequence, its quantity in the cell, andits mode of inheritance. The nucleus of the cell contains two sets of 23chromosomes, one paternal set and one maternal set. However, cells maycontain hundreds to thousands of mitochondria, each of which may containseveral copies of mtDNA. Nuclear DNA has many more bases than mtDNA, butmtDNA is present in many more copies than nuclear DNA. Thischaracteristic of mtDNA is useful in situations where the amount of DNAin a sample is very limited. Typical sources of DNA recovered from crimescenes include hair, bones, teeth, and body fluids such as saliva,semen, and blood.

In humans, mitochondrial DNA is inherited strictly from the mother (CaseJ. T. and Wallace, D. C., Somatic Cell Genetics, 1981, 7, 103-108;Giles, R. E. et al. Proc. Natl. Acad. Sci. 1980, 77, 6715-6719;Hutchison, C. A. et al. Nature, 1974, 251, 536-538). Thus, the mtDNAsequences obtained from maternally related individuals, such as abrother and a sister or a mother and a daughter, will exactly match eachother in the absence of a mutation. This characteristic of mtDNA isadvantageous in missing persons cases as reference mtDNA samples can besupplied by any maternal relative of the missing individual (Ginther, C.et al. Nature Genetics, 1992, 2, 135-138; Holland, M. M. et al. Journalof Forensic Sciences, 1993, 38, 542-553; Stoneking, M. et al. AmericanJournal of Human Genetics, 1991, 48, 370-382).

The human mtDNA genome is approximately 16,569 bases in length and hastwo general regions: the coding region and the control region. Thecoding region is responsible for the production of various biologicalmolecules involved in the process of energy production in the cell. Thecontrol region is responsible for regulation of the mtDNA molecule. Tworegions of mtDNA within the control region have been found to be highlypolymorphic, or variable, within the human population (Greenberg, B. D.et al. Gene, 1983, 21, 33-49). These two regions are termed“hypervariable Region I” (HVR1), which has an approximate length of 342base pairs (bp), and “hypervariable Region II” (HVR2), which has anapproximate length of 268 bp. Forensic mtDNA examinations are performedusing these two regions because of the high degree of variability foundamong individuals.

Approximately 610 bp of mtDNA are currently sequenced in forensic mtDNAanalysis. Recording and comparing mtDNA sequences would be difficult andpotentially confusing if all of the bases were listed. Thus, mtDNAsequence information is recorded by listing only the differences withrespect to a reference DNA sequence. By convention, human mtDNAsequences are described using the first complete published mtDNAsequence as a reference (Anderson, S. et al., Nature, 1981, 290,457-465). This sequence is commonly referred to as the Andersonsequence. It is also called the Cambridge reference sequence or theOxford sequence. Each base pair in this sequence is assigned a number.Deviations from this reference sequence are recorded as the number ofthe position demonstrating a difference and a letter designation of thedifferent base. For example, a transition from A to G at Position 263would be recorded as 263 G. If deletions or insertions of bases arepresent in the mtDNA, these differences are denoted as well.

In the United States, there are seven laboratories currently conductingforensic mtDNA examinations: the FBI Laboratory; Laboratory Corporationof America (LabCorp) in Research Triangle Park, North Carolina;Mitotyping Technologies in State College, Pa.; the Bode Technology Group(BTG) in Springfield, Va.; the Armed Forces DNA IdentificationLaboratory (AFDIL) in Rockville, Md.; BioSynthesis, Inc. in Lewisville,Texas; and Reliagene in New Orleans, La.

Mitochondrial DNA analyses have been admitted in criminal proceedingsfrom these laboratories in the following states as of April 1999:Alabama, Arkansas, Florida, Indiana, Illinois, Maryland, Michigan, NewMexico, North Carolina, Pennsylvania, South Carolina, Tennessee, Texas,and Washington. Mitochondrial DNA has also been admitted and used incriminal trials in Australia, the United Kingdom, and several otherEuropean countries.

Since 1996, the number of individuals performing mitochondrial DNAanalysis at the FBI Laboratory has grown from 4 to 12, with morepersonnel expected in the near future. Over 150 mitochondrial DNA caseshave been completed by the FBI Laboratory as of March 1999, and dozensmore await analysis. Forensic courses are being taught by the FBILaboratory personnel and other groups to educate forensic scientists inthe procedures and interpretation of mtDNA sequencing. More and moreindividuals are learning about the value of mtDNA sequencing forobtaining useful information from evidentiary samples that are small,degraded, or both. Mitochondrial DNA sequencing is becoming known notonly as an exclusionary tool but also as a complementary technique foruse with other human identification procedures. Mitochondrial DNAanalysis will continue to be a powerful tool for law enforcementofficials in the years to come as other applications are developed,validated, and applied to forensic evidence.

Presently, the forensic analysis of mtDNA is rigorous andlabor-intensive. Currently, only 1-2 cases per month per analyst can beperformed. Several molecular biological techniques are combined toobtain a mtDNA sequence from a sample. The steps of the mtDNA analysisprocess include primary visual analysis, sample preparation, DNAextraction, polymerase chain reaction (PCR) amplification,postamplification quantification of the DNA, automated DNA sequencing,and data analysis. Another complicating factor in the forensic analysisof mtDNA is the occurrence of heteroplasmy wherein the pool of mtDNAs ina given cell is heterogeneous due to mutations in individual mtDNAs.There are two forms of heteroplasmy found in mtDNA. Sequenceheteroplasmy (also known as point heteroplasmy) is the occurrence ofmore than one base at a particular position or positions in the mtDNAsequence. Length heteroplasmy is the occurrence of more than one lengthof a stretch of the same base in a mtDNA sequence as a result ofinsertion of nucleotide residues. Heteroplasmy is a problem for forensicinvestigators since a sample from a crime scene can differ from a samplefrom a suspect by one base pair and this difference may be interpretedas sufficient evidence to eliminate that individual as the suspect. Hairsamples from a single individual can contain heteroplasmic mutations atvastly different concentrations and even the root and shaft of a singlehair can differ. The detection methods currently available to molecularbiologists cannot detect low levels of heteroplasmy. Furthermore, ifpresent, length heteroplasmy will adversely affect sequencing runs byresulting in an out-of-frame sequence that cannot be interpreted.

Mass spectrometry provides detailed information about the moleculesbeing analyzed, including high mass accuracy. It is also a process thatcan be easily automated. Low-resolution MS may be unreliable when usedto detect some known agents, if their spectral lines are sufficientlyweak or sufficiently close to those from other living organisms in thesample. DNA chips with specific probes can only determine the presenceor absence of specifically anticipated organisms. Because there arehundreds of thousands of species of benign bacteria, some very similarin sequence to threat organisms, even arrays with 10,000 probes lack thebreadth needed to detect a particular organism.

Antibodies face more severe diversity limitations than arrays. Ifantibodies are designed against highly conserved targets to increasediversity, the false alarm problem will dominate, again because threatorganisms are very similar to benign ones. Antibodies are only capableof detecting known agents in relatively uncluttered environments.

Several groups have described detection of PCR products using highresolution electrospray ionization-Fourier transform-ion cyclotronresonance mass spectrometry (ESI-FT-ICR MS). Accurate measurement ofexact mass combined with knowledge of the number of at least onenucleotide allowed calculation of the total base composition for PCRduplex products of approximately 100 base pairs. (Aaserud et al., J. Am.Soc. Mass Spec., 1996, 7, 1266-1269; Muddiman et al., Anal. Chem., 1997,69, 1543-1549; Wunschel et al., Anal. Chem., 1998, 70, 1203-1207;Muddiman et al., Rev. Anal. Chem., 1998, 17, 1-68). Electrosprayionization-Fourier transform-ion cyclotron resistance (ESI-FT-ICR) MSmay be used to determine the mass of double-stranded, 500 base-pair PCRproducts via the average molecular mass (Hurst et al., Rapid Commun.Mass Spec. 1996, 10, 377-382). The use of matrix-assisted laserdesorption ionization-time of flight (MALDI-TOF) mass spectrometry forcharacterization of PCR products has been described. (Muddiman et al.,Rapid Commun. Mass Spec., 1999, 13, 1201-1204). However, the degradationof DNAs over about 75 nucleotides observed with MALDI limited theutility of this method.

U.S. Pat. No. 5,849,492 describes a method for retrieval ofphylogenetically informative DNA sequences which comprise searching fora highly divergent segment of genomic DNA surrounded by two highlyconserved segments, designing the universal primers for PCRamplification of the highly divergent region, amplifying the genomic DNAby PCR technique using universal primers, and then sequencing the geneto determine the identity of the organism.

U.S. Pat. No. 5,965,363 discloses methods for screening nucleic acidsfor polymorphisms by analyzing amplified target nucleic acids using massspectrometric techniques and to procedures for improving mass resolutionand mass accuracy of these methods.

WO 99/14375 describes methods, PCR primers and kits for use in analyzingpreselected DNA tandem nucleotide repeat alleles by mass spectrometry.

WO 98/12355 discloses methods of determining the mass of a targetnucleic acid by mass spectrometric analysis, by cleaving the targetnucleic acid to reduce its length, making the target single-stranded andusing MS to determine the mass of the single-stranded shortened target.Also disclosed are methods of preparing a double-stranded target nucleicacid for MS analysis comprising amplification of the target nucleicacid, binding one of the strands to a solid support, releasing thesecond strand and then releasing the first strand which is then analyzedby MS. Kits for target nucleic acid preparation are also provided.

PCT WO97/33000 discloses methods for detecting mutations in a targetnucleic acid by nonrandomly fragmenting the target into a set ofsingle-stranded nonrandom length fragments and determining their massesby MS.

U.S. Pat. No. 5,605,798 describes a fast and highly accurate massspectrometer-based process for detecting the presence of a particularnucleic acid in a biological sample for diagnostic purposes.

WO 98/21066 describes processes for determining the sequence of aparticular target nucleic acid by mass spectrometry. Processes fordetecting a target nucleic acid present in a biological sample by PCRamplification and mass spectrometry detection are disclosed, as aremethods for detecting a target nucleic acid in a sample by amplifyingthe target with primers that contain restriction sites and tags,extending and cleaving the amplified nucleic acid, and detecting thepresence of extended product, wherein the presence of a DNA fragment ofa mass different from wild-type is indicative of a mutation. Methods ofsequencing a nucleic acid via mass spectrometry methods are alsodescribed.

WO 97/37041, WO 99/31278 and U.S. Pat. No. 5,547,835 describe methods ofsequencing nucleic acids using mass spectrometry. U.S. Pat. Nos.5,622,824, 5,872,003 and 5,691,141 describe methods, systems and kitsfor exonuclease-mediated mass spectrometric sequencing.

Thus, there is a need for a method for bioagent detection andidentification which is both specific and rapid, and in which no nucleicacid sequencing is required. The present invention addresses this need.

SUMMARY OF THE INVENTION

The present invention is directed to methods of identifying anindividual by obtaining mitochondrial DNA from the individual,amplifying the mitochondrial DNA with intelligent primers to obtain atleast one amplification product, determining the molecular mass of theamplification product and comparing the molecular mass with a databaseof molecular masses calculated from known sequences of mitochondrialDNAs indexed to known individuals, wherein a match between saidmolecular mass of the amplification product and the calculated molecularmass of a known sequence in the database identifies the individual.

Furthermore, this present invention is directed to methods ofdetermining the identity of protists or fungi by a process analogous tothe process described above, and determining the geographic spread offungi and protists by analysis of samples obtained from a plurality ofgeographic locations.

The present invention is also directed to methods of characterizing theheteroplasmy of a sample of mitochondrial DNA by amplifying themitochondrial DNA with intelligent primers to obtain a plurality ofamplification products, determining the molecular masses and relativeabundances of the plurality of amplification products, therebycharacterizing said heteroplasmy. Furthermore, the present invention isdirected to using these methods to characterize the heteroplasmy of aplurality of samples of mitochondrial DNA taken from an individual atdifferent points of the lifetime of said individual to investigate therate of naturally occurring mutations in mitochondrial DNA. Thesemethods can also be used to initiate a prediction of the rate of onsetof mitochondrial disease.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A-1H and FIG. 2 are consensus diagrams that show examples ofconserved regions from 16S rRNA (FIG. 1A-1, 1A-2, 1A-3, 1A-4, and 1A-5),23S rRNA (3′-half, FIGS. 1B, 1C, and 1D; 5′-half, FIG. 1E-F), 23S rRNADomain I (FIG. 1G), 23S rRNA Domain IV (FIG. 1H) and 16S rRNA Domain III(FIG. 2) which are suitable for use in the present invention. Lines witharrows are examples of regions to which intelligent primer pairs for PCRare designed. The label for each primer pair represents the starting andending base number of the amplified region on the consensus diagram.Bases in capital letters are greater than 95% conserved; bases in lowercase letters are 90-95% conserved, filled circles are 80-90% conserved;and open circles are less than 80% conserved. The label for each primerpair represents the starting and ending base number of the amplifiedregion on the consensus diagram. The nucleotide sequence of the 16S rRNAconsensus sequence is SEQ ID NO:3 and the nucleotide sequence of the 23SrRNA consensus sequence is SEQ ID NO:4.

FIG. 2 shows a typical primer amplified region from the 16S rRNA DomainIII shown in FIG. 1A-1.

FIG. 3 is a schematic diagram showing conserved regions in RNase P.Bases in capital letters are greater than 90% conserved; bases in lowercase letters are 80-90% conserved; filled circles designate bases whichare 70-80% conserved; and open circles designate bases that are lessthan 70% conserved.

FIG. 4 is a schematic diagram of base composition signaturedetermination using nucleotide analog “tags” to determine basecomposition signatures.

FIG. 5 shows the deconvoluted mass spectra of a Bacillus anthracisregion with and without the mass tag phosphorothioate A (A*). The twospectra differ in that the measured molecular weight of the masstag-containing sequence is greater than the unmodified sequence.

FIG. 6 shows base composition signature (BCS) spectra from PCR productsfrom Staphylococcus aureus (S. aureus 16S_(—)1337F) and Bacillusanthracis (B. anthr. 16S_(—)1337F), amplified using the same primers.The two strands differ by only two (AT—>CG) substitutions and areclearly distinguished on the basis of their BCS.

FIG. 7 shows that a single difference between two sequences (A14 in B.anthracis vs. A15 in B. cereus) can be easily detected using ESI-TOFmass spectrometry.

FIG. 8 is an ESI-TOF of Bacillus anthracis spore coat protein sspE 56merplus calibrant. The signals unambiguously identify B. anthracis versusother Bacillus species.

FIG. 9 is an ESI-TOF of a B. anthracis synthetic 16S_(—)1228 duplex(reverse and forward strands). The technique easily distinguishesbetween the forward and reverse strands.

FIG. 10 is an ESI-FTICR-MS of a synthetic B. anthracis 16S_(—)1337 46base pair duplex.

FIG. 11 is an ESI-TOF-MS of a 56mer oligonucleotide (3 scans) from theB. anthracis saspB gene with an internal mass standard. The internalmass standards are designated by asterisks.

FIG. 12 is an ESI-TOF-MS of an internal standard with 5 mM TBA-TFAbuffer showing that charge stripping with tributylammoniumtrifluoroacetate reduces the most abundant charge state from [M-8H+]8−to [M-3H+]3−.

FIG. 13 is a portion of a secondary structure defining databaseaccording to one embodiment of the present invention, where two examplesof selected sequences are displayed graphically thereunder.

FIG. 14 is a three dimensional graph demonstrating the grouping ofsample molecular weight according to species.

FIG. 15 is a three dimensional graph demonstrating the grouping ofsample molecular weights according to species of virus and mammalinfected.

FIG. 16 is a three dimensional graph demonstrating the grouping ofsample molecular weights according to species of virus, andanimal-origin of infectious agent.

FIG. 17 is a figure depicting how the triangulation method of thepresent invention provides for the identification of an unknown bioagentwithout prior knowledge of the unknown agent. The use of differentprimer sets to distinguish and identify the unknown is also depicted asprimer sets I, II and III within this figure. A three dimensional graphdepicts all of bioagent space (170), including the unknown bioagent,which after use of primer set I (171) according to a method according tothe present invention further differentiates and classifies bioagentsaccording to major classifications (176) which, upon further analysisusing primer set II (172) differentiates the unknown agent (177) fromother, known agents (173) and finally, the use of a third primer set(175) further specifies subgroups within the family of the unknown(174).

FIG. 18 shows: a) a representative ESI-FTICR mass spectrum of arestriction digest of a 986 bp region of the 16S ribosomal gene from E.coli K12 digested with a mixture of BstNI, BsmFI, BfaI, and NcoI; b) adeconvoluted representation (neutral mass) of the above spectrum showingthe base compositions derived from accurate mass measurements of eachfragment; and c) a representative reconstructed restriction map showingcomplete base composition coverage for nucleotides 1-856. The Nco1 didnot cut.

FIG. 19 indicates the process of mtDNA analysis. After amplification byPCR (210), the PCR products were subjected to restriction digests (220)with RsaI for HVR1 and a combination of HpaII, HpyCH4IV, PacI and EaeIfor HVR2 in order to obtain amplicon segments suitable for analysis byFTICR-MS (240). The data were processed to obtain mass data for eachamplicon segment (250) which were then compared to the masses calculatedfor theoretical digests from the FBI mtDNA database by a scoring scheme(260).

FIG. 20A indicates predicted and actual mass data with scoringparameters for length heteroplasmy (HVR1-1-outer-variants 1 and 2) inthe digest segment from position 94 to 145 (variant 1)/146 (variant 2)are shown.

FIG. 20B indicates that, whereas sequencing fails to resolve thevariants due to the length heteroplasmy, mass determination detectsmultiple species simultaneously and also indicates abundance ratios. Inthis case, the ratio of variant 1 to variant 2 (short to long alleles)is 1:3.

DESCRIPTION OF EMBODIMENTS A. Introduction

The present invention provides, inter alia, methods for detection andidentification of bioagents in an unbiased manner using “bioagentidentifying amplicons.” “Intelligent primers” are selected to hybridizeto conserved sequence regions of nucleic acids derived from a bioagentand which bracket variable sequence regions to yield a bioagentidentifying amplicon which can be amplified and which is amenable tomolecular mass determination. The molecular mass then provides a meansto uniquely identify the bioagent without a requirement for priorknowledge of the possible identity of the bioagent. The molecular massor corresponding “base composition signature” (BCS) of the amplificationproduct is then matched against a database of molecular masses or basecomposition signatures. Furthermore, the method can be applied to rapidparallel “multiplex” analyses, the results of which can be employed in atriangulation identification strategy. The present method provides rapidthroughput and does not require nucleic acid sequencing of the amplifiedtarget sequence for bioagent detection and identification.

B. Bioagents

In the context of this invention, a “bioagent” is any organism, cell, orvirus, living or dead, or a nucleic acid derived from such an organism,cell or virus. Examples of bioagents include, but are not limited, tocells, including but not limited to, cells, including but not limited tohuman clinical samples, bacterial cells and other pathogens) viruses,fungi, and protists, parasites, and pathogenicity markers (including butnot limited to: pathogenicity islands, antibiotic resistance genes,virulence factors, toxin genes and other bioregulating compounds).Samples may be alive or dead or in a vegetative state (for example,vegetative bacteria or spores) and may be encapsulated or bioengineered.In the context of this invention, a “pathogen” is a bioagent whichcauses a disease or disorder.

Despite enormous biological diversity, all forms of life on earth sharesets of essential, common features in their genomes. Bacteria, forexample have highly conserved sequences in a variety of locations ontheir genomes. Most notable is the universally conserved region of theribosome. but there are also conserved elements in other non-codingRNAs, including RNAse P and the signal recognition particle (SRP) amongothers. Bacteria have a common set of absolutely required genes. About250 genes are present in all bacterial species (Proc. Nail. Acad. Sci.U.S.A., 1996, 93, 10268; Science, 1995, 270, 397), including tinygenomes like Mycoplasma, Ureaplasma and Rickettsia. These genes encodeproteins involved in translation, replication, recombination and repair,transcription, nucleotide metabolism, amino acid metabolism, lipidmetabolism, energy generation, uptake, secretion and the like. Examplesof these proteins are DNA polymerase III beta, elongation factor TU,heat shock protein groEL, RNA polymerase beta, phosphoglycerate kinase,NADH dehydrogenase, DNA ligase, DNA topoisomerase and elongation factorG. Operons can also be targeted using the present method. One example ofan operon is the bfp operon from enteropathogenic E. coli. Multiple corechromosomal genes can be used to classify bacteria at a genus or genusspecies level to determine if an organism has threat potential. Themethods can also be used to detect pathogenicity markers (plasmid orchromosomal) and antibiotic resistance genes to confirm the threatpotential of an organism and to direct countermeasures.

C. Selection of “Bioagent Identifying Amplicons”

Since genetic data provide the underlying basis for identification ofbioagents by the methods of the present invention, it is necessary toselect segments of nucleic acids which ideally provide enoughvariability to distinguish each individual bioagent and whose molecularmass is amenable to molecular mass determination. In one embodiment ofthe present invention, at least one polynucleotide segment is amplifiedto facilitate detection and analysis in the process of identifying thebioagent. Thus, the nucleic acid segments which provide enoughvariability to distinguish each individual bioagent and whose molecularmasses are amenable to molecular mass determination are herein describedas “bioagent identifying amplicons.” The term “amplicon” as used herein,refers to a segment of a polynucleotide which is amplified in anamplification reaction.

As used herein, “intelligent primers” are primers that are designed tobind to highly conserved sequence regions of a bioagent identifyingamplicon that flank an intervening variable region and yieldamplification products which ideally provide enough variability todistinguish each individual bioagent, and which are amenable tomolecular mass analysis. By the term “highly conserved,” it is meantthat the sequence regions exhibit between about 80-100%, or betweenabout 90-100%, or between about 95-100% identity. The molecular mass ofa given amplification product provides a means of identifying thebioagent from which it was obtained, due to the variability of thevariable region. Thus design of intelligent primers requires selectionof a variable region with appropriate variability to resolve theidentity of a given bioagent. Bioagent identifying amplicons are ideallyspecific to the identity of the bioagent. A plurality of bioagentidentifying amplicons selected in parallel for distinct bioagents whichcontain the same conserved sequences for hybridization of the same pairof intelligent primers are herein defined as “correlative bioagentidentifying amplicons.”

In one embodiment, the bioagent identifying amplicon is a portion of aribosomal RNA (rRNA) gene sequence. With the complete sequences of manyof the smallest microbial genomes now available, it is possible toidentify a set of genes that defines “minimal life” and identifycomposition signatures that uniquely identify each gene and organism.Genes that encode core life functions such as DNA replication,transcription, ribosome structure, translation, and transport aredistributed broadly in the bacterial genome and are suitable regions forselection of bioagent identifying amplicons. Ribosomal RNA (rRNA) genescomprise regions that provide useful base composition signatures. Likemany genes involved in core life functions, rRNA genes contain sequencesthat are extraordinarily conserved across bacterial domains interspersedwith regions of high variability that are more specific to each species.The variable regions can be utilized to build a database of basecomposition signatures. The strategy involves creating a structure-basedalignment of sequences of the small (16S) and the large (23S) subunitsof the rRNA genes. For example, there are currently over 13,000sequences in the ribosomal RNA database that has been created andmaintained by Robin Gutell, University of Texas at Austin, and ispublicly available on the Institute for Cellular and Molecular Biologyweb page on the world wide web of the Internet at, for example,“rna.icmb.utexas.edu/.” There is also a publicly available rRNA databasecreated and maintained by the University of Antwerp, Belgium on theworld wide web of the Internet at, for example, “rrna.uia.ac.be.”

These databases have been analyzed to determine regions that are usefulas bioagent identifying amplicons. The characteristics of such regionsinclude: a) between about 80 and 100%, or greater than about 95%identity among species of the particular bioagent of interest, ofupstream and downstream nucleotide sequences which serve as sequenceamplification primer sites; b) an intervening variable region whichexhibits no greater than about 5% identity among species; and c) aseparation of between about 30 and 1000 nucleotides, or no more thanabout 50-250 nucleotides, or no more than about 60-100 nucleotides,between the conserved regions.

As a non-limiting example, for identification of Bacillus species, theconserved sequence regions of the chosen bioagent identifying ampliconmust be highly conserved among all Bacillus species while the variableregion of the bioagent identifying amplicon is sufficiently variablesuch that the molecular masses of the amplification products of allspecies of Bacillus are distinguishable.

Bioagent identifying amplicons amenable to molecular mass determinationare either of a length, size or mass compatible with the particular modeof molecular mass determination or compatible with a means of providinga predictable fragmentation pattern in order to obtain predictablefragments of a length compatible with the particular mode of molecularmass determination. Such means of providing a predictable fragmentationpattern of an amplification product include, but are not limited to,cleavage with restriction enzymes or cleavage primers, for example.

Identification of bioagents can be accomplished at different levelsusing intelligent primers suited to resolution of each individual levelof identification. “Broad range survey” intelligent primers are designedwith the objective of identifying a bioagent as a member of a particulardivision of bioagents. A “bioagent division” is defined as group ofbioagents above the species level and includes but is not limited to:orders, families, classes, clades, genera or other such groupings ofbioagents above the species level. As a non-limiting example, members ofthe Bacillus/Clostridia group or gamma-proteobacteria group may beidentified as such by employing broad range survey intelligent primerssuch as primers which target 16S or 23S ribosomal RNA.

In some embodiments, broad range survey intelligent primers are capableof identification of bioagents at the species level. One main advantageof the detection methods of the present invention is that the broadrange survey intelligent primers need not be specific for a particularbacterial species, or even genus, such as Bacillus or Streptomyces.Instead, the primers recognize highly conserved regions across hundredsof bacterial species including, but not limited to, the speciesdescribed herein. Thus, the same broad range survey intelligent primerpair can be used to identify any desired bacterium because it will bindto the conserved regions that flank a variable region specific to asingle species, or common to several bacterial species, allowingunbiased nucleic acid amplification of the intervening sequence anddetermination of its molecular weight and base composition. For example,the 16S_(—)971-1062, 16S_(—)1228-1310 and 16S_(—)1100-1188 regions are98-99% conserved in about 900 species of bacteria (16S=16S rRNA, numbersindicate nucleotide position). In one embodiment of the presentinvention, primers used in the present method bind to one or more ofthese regions or portions thereof.

Due to their overall conservation, the flanking rRNA primer sequencesserve as good intelligent primer binding sites to amplify the nucleicacid region of interest for most, if not all, bacterial species. Theintervening region between the sets of primers varies in length and/orcomposition, and thus provides a unique base composition signature.Examples of intelligent primers that amplify regions of the 16S and 23SrRNA are shown in FIGS. 1A-1H. A typical primer amplified region in 16SrRNA is shown in FIG. 2. The arrows represent primers that bind tohighly conserved regions which flank a variable region in 16S rRNAdomain III. The amplified region is the stem-loop structure under“1100-1188.” It is advantageous to design the broad range surveyintelligent primers to minimize the number of primers required for theanalysis, and to allow detection of multiple members of a bioagentdivision using a single pair of primers. The advantage of using broadrange survey intelligent primers is that once a bioagent is broadlyidentified, the process of further identification at species andsub-species levels is facilitated by directing the choice of additionalintelligent primers.

“Division-wide” intelligent primers are designed with an objective ofidentifying a bioagent at the species level. As a non-limiting example,a Bacillus anthracis, Bacillus cereus and Bacillus thuringiensis can bedistinguished from each other using division-wide intelligent primers.Division-wide intelligent primers are not always required foridentification at the species level because broad range surveyintelligent primers may provide sufficient identification resolution toaccomplishing this identification objective.

“Drill-down” intelligent primers are designed with an objective ofidentifying a sub-species characteristic of a bioagent. A “sub-speciescharacteristic” is defined as a property imparted to a bioagent at thesub-species level of identification as a result of the presence orabsence of a particular segment of nucleic acid. Such sub-speciescharacteristics include, but are not limited to, strains, sub-types,pathogenicity markers such as antibiotic resistance genes, pathogenicityislands, toxin genes and virulence factors. Identification of suchsub-species characteristics is often critical for determining properclinical treatment of pathogen infections.

Chemical Modifications of Intelligent Primers

Ideally, intelligent primer hybridization sites are highly conserved inorder to facilitate the hybridization of the primer. In cases whereprimer hybridization is less efficient due to lower levels ofconservation of sequence, intelligent primers can be chemically modifiedto improve the efficiency of hybridization.

For example, because any variation (due to codon wobble in the 3^(rd)position) in these conserved regions among species is likely to occur inthe third position of a DNA triplet, oligonucleotide primers can bedesigned such that the nucleotide corresponding to this position is abase which can bind to more than one nucleotide, referred to herein as a“universal base.” For example, under this “wobble” pairing, inosine (I)binds to U, C or A; guanine (G) binds to U or C, and uridine (U) bindsto U or C. Other examples of universal bases include nitroindoles suchas 5-nitroindole or 3-nitropyrrole (Loakes et al., Nucleosides andNucleotides, 1995, 14, 1001-1003), the degenerate nucleotides dP or dK(Hill et al.), an acyclic nucleoside analog containing 5-nitroindazole(Van Aerschot et al., Nucleosides and Nucleotides, 1995, 14, 1053-1056)or the purine analog1-(2-deoxy-β-D-ribofuranosyl)-imidazole-4-carboxamide (Sala et al.,Nucl. Acids Res., 1996, 24, 3302-3306).

In another embodiment of the invention, to compensate for the somewhatweaker binding by the “wobble” base, the oligonucleotide primers aredesigned such that the first and second positions of each triplet areoccupied by nucleotide analogs which bind with greater affinity than theunmodified nucleotide. Examples of these analogs include, but are notlimited to, 2,6-diaminopurine which binds to thymine, propyne T whichbinds to adenine and propyne C and phenoxazines, including G-clamp,which binds to G. Propynylated pyrimidines are described in U.S. Pat.Nos. 5,645,985, 5,830,653 and 5,484,908, each of which is commonly ownedand incorporated herein by reference in its entirety. Propynylatedprimers are claimed in U.S. Ser. No. 10/294,203 which is also commonlyowned and incorporated herein by reference in entirety. Phenoxazines aredescribed in U.S. Pat. Nos. 5,502,177, 5,763,588, and 6,005,096, each ofwhich is incorporated herein by reference in its entirety. G-clamps aredescribed in U.S. Pat. Nos. 6,007,992 and 6,028,183, each of which isincorporated herein by reference in its entirety.

D. Characterization of Bioagent Identifying Amplicons

A theoretically ideal bioagent detector would identify, quantify, andreport the complete nucleic acid sequence of every bioagent that reachedthe sensor. The complete sequence of the nucleic acid component of apathogen would provide all relevant information about the threat,including its identity and the presence of drug-resistance orpathogenicity markers. This ideal has not yet been achieved. However,the present invention provides a straightforward strategy for obtaininginformation with the same practical value based on analysis of bioagentidentifying amplicons by molecular mass determination.

In some cases, a molecular mass of a given bioagent identifying ampliconalone does not provide enough resolution to unambiguously identify agiven bioagent. For example, the molecular mass of the bioagentidentifying amplicon obtained using the intelligent primer pair“16S_(—)971” would be 55622 Da for both E. coli and Salmonellatyphimurium. However, if additional intelligent primers are employed toanalyze additional bioagent identifying amplicons, a “triangulationidentification” process is enabled. For example, the “16S_(—)1100”intelligent primer pair yields molecular masses of 55009 and 55005 Dafor E. coli and Salmonella typhimurium, respectively. Furthermore, the“23S_(—)855” intelligent primer pair yields molecular masses of 42656and 42698 Da for E. coli and Salmonella typhimurium, respectively. Inthis basic example, the second and third intelligent primer pairsprovided the additional “fingerprinting” capability or resolution todistinguish between the two bioagents.

In another embodiment, the triangulation identification process ispursued by measuring signals from a plurality of bioagent identifyingamplicons selected within multiple core genes. This process is used toreduce false negative and false positive signals, and enablereconstruction of the origin of hybrid or otherwise engineeredbioagents. In this process, after identification of multiple core genes,alignments are created from nucleic acid sequence databases. Thealignments are then analyzed for regions of conservation and variation,and bioagent identifying amplicons are selected to distinguish bioagentsbased on specific genomic differences. For example, identification ofthe three part toxin genes typical of B. anthracis (Bowen et al., J.Appl. Microbiol., 1999, 87, 270-278) in the absence of the expectedsignatures from the B. anthracis genome would suggest a geneticengineering event.

The triangulation identification process can be pursued bycharacterization of bioagent identifying amplicons in a massivelyparallel fashion using the polymerase chain reaction (PCR), such asmultiplex PCR, and mass spectrometric (MS) methods. Sufficientquantities of nucleic acids should be present for detection of bioagentsby MS. A wide variety of techniques for preparing large amounts ofpurified nucleic acids or fragments thereof are well known to those ofskill in the art. PCR requires one or more pairs of oligonucleotideprimers that bind to regions which flank the target sequence(s) to beamplified. These primers prime synthesis of a different strand of DNA,with synthesis occurring in the direction of one primer towards theother primer. The primers, DNA to be amplified, a thermostable DNApolymerase (e.g. Taq polymerase), the four deoxynucleotidetriphosphates, and a buffer are combined to initiate DNA synthesis. Thesolution is denatured by heating, then cooled to allow annealing ofnewly added primer, followed by another round of DNA synthesis. Thisprocess is typically repeated for about 30 cycles, resulting inamplification of the target sequence.

Although the use of PCR is suitable, other nucleic acid amplificationtechniques may also be used, including ligase chain reaction (LCR) andstrand displacement amplification (SDA). The high-resolution MStechnique allows separation of bioagent spectral lines from backgroundspectral lines in highly cluttered environments.

In another embodiment, the detection scheme for the PCR productsgenerated from the bioagent(s) incorporates at least three features.First, the technique simultaneously detects and differentiates multiple(generally about 6-10) PCR products. Second, the technique provides amolecular mass that uniquely identifies the bioagent from the possibleprimer sites. Finally, the detection technique is rapid, allowingmultiple PCR reactions to be run in parallel.

E. Mass Spectrometric Characterization of Bioagent Identifying Amplicons

Mass spectrometry (MS)-based detection of PCR products provides a meansfor determination of BCS which has several advantages. MS isintrinsically a parallel detection scheme without the need forradioactive or fluorescent labels, since every amplification product isidentified by its molecular mass. The current state of the art in massspectrometry is such that less than femtomole quantities of material canbe readily analyzed to afford information about the molecular contentsof the sample. An accurate assessment of the molecular mass of thematerial can be quickly obtained, irrespective of whether the molecularweight of the sample is several hundred, or in excess of one hundredthousand atomic mass units (amu) or Daltons. Intact molecular ions canbe generated from amplification products using one of a variety ofionization techniques to convert the sample to gas phase. Theseionization methods include, but are not limited to, electrosprayionization (ES), matrix-assisted laser desorption ionization (MALDI) andfast atom bombardment (FAB). For example, MALDI of nucleic acids, alongwith examples of matrices for use in MALDI of nucleic acids, aredescribed in WO 98/54751 (Genetrace, Inc.).

In some embodiments, large DNAs and RNAs, or large amplificationproducts therefrom, can be digested with restriction endonucleases priorto ionization. Thus, for example, an amplification product that was 10kDa could be digested with a series of restriction endonucleases toproduce a panel of, for example, 100 Da fragments. Restrictionendonucleases and their sites of action are well known to the skilledartisan. In this manner, mass spectrometry can be performed for thepurposes of restriction mapping.

Upon ionization, several peaks are observed from one sample due to theformation of ions with different charges. Averaging the multiplereadings of molecular mass obtained from a single mass spectrum affordsan estimate of molecular mass of the bioagent. Electrospray ionizationmass spectrometry (ESI-MS) is particularly useful for very highmolecular weight polymers such as proteins and nucleic acids havingmolecular weights greater than 10 kDa, since it yields a distribution ofmultiply-charged molecules of the sample without causing a significantamount of fragmentation.

The mass detectors used in the methods of the present invention include,but are not limited to, Fourier transform ion cyclotron resonance massspectrometry (FT-ICR-MS), ion trap, quadrupole, magnetic sector, time offlight (TOF), Q-TOF, and triple quadrupole.

In general, the mass spectrometric techniques which can be used in thepresent invention include, but are not limited to, tandem massspectrometry, infrared multiphoton dissociation and pyrolytic gaschromatography mass spectrometry (PGC-MS). In one embodiment of theinvention, the bioagent detection system operates continually inbioagent detection mode using pyrolytic GC-MS without PCR for rapiddetection of increases in biomass (for example, increases in fecalcontamination of drinking water or of germ warfare agents). To achieveminimal latency, a continuous sample stream flows directly into thePGC-MS combustion chamber. When an increase in biomass is detected, aPCR process is automatically initiated. Bioagent presence produceselevated levels of large molecular fragments from, for example, about100-7,000 Da which are observed in the PGC-MS spectrum. The observedmass spectrum is compared to a threshold level and when levels ofbiomass are determined to exceed a predetermined threshold, the bioagentclassification process described hereinabove (combining PCR and MS, suchas FT-ICR MS) is initiated. Optionally, alarms or other processes(halting ventilation flow, physical isolation) are also initiated bythis detected biomass level.

The accurate measurement of molecular mass for large DNAs is limited bythe adduction of cations from the PCR reaction to each strand,resolution of the isotopic peaks from natural abundance ¹³C and ¹⁵Nisotopes, and assignment of the charge state for any ion. The cationsare removed by in-line dialysis using a flow-through chip that bringsthe solution containing the PCR products into contact with a solutioncontaining ammonium acetate in the presence of an electric fieldgradient orthogonal to the flow. The latter two problems are addressedby operating with a resolving power of >100,000 and by incorporatingisotopically depleted nucleotide triphosphates into the DNA. Theresolving power of the instrument is also a consideration. At aresolving power of 10,000, the modeled signal from the [M-14H+]¹⁴⁻charge state of an 84mer PCR product is poorly characterized andassignment of the charge state or exact mass is impossible. At aresolving power of 33,000, the peaks from the individual isotopiccomponents are visible. At a resolving power of 100,000, the isotopicpeaks are resolved to the baseline and assignment of the charge statefor the ion is straightforward. The [¹³C,¹⁵N]-depleted triphosphates areobtained, for example, by growing microorganisms on depleted media andharvesting the nucleotides (Batey et al., Nucl. Acids Res., 1992, 20,4515-4523).

While mass measurements of intact nucleic acid regions are believed tobe adequate to determine most bioagents, tandem mass spectrometry(MS^(n)) techniques may provide more definitive information pertainingto molecular identity or sequence. Tandem MS involves the coupled use oftwo or more stages of mass analysis where both the separation anddetection steps are based on mass spectrometry. The first stage is usedto select an ion or component of a sample from which further structuralinformation is to be obtained. The selected ion is then fragmentedusing, e.g., blackbody irradiation, infrared multiphoton dissociation,or collisional activation. For example, ions generated by electrosprayionization (ESI) can be fragmented using IR multiphoton dissociation.This activation leads to dissociation of glycosidic bonds and thephosphate backbone, producing two series of fragment ions, called thew-series (having an intact 3′ terminus and a 5′ phosphate followinginternal cleavage) and the a-Base series (having an intact 5′ terminusand a 3′ furan).

The second stage of mass analysis is then used to detect and measure themass of these resulting fragments of product ions. Such ion selectionfollowed by fragmentation routines can be performed multiple times so asto essentially completely dissect the molecular sequence of a sample.

If there are two or more targets of similar molecular mass, or if asingle amplification reaction results in a product which has the samemass as two or more bioagent reference standards, they can bedistinguished by using mass-modifying “tags.” In this embodiment of theinvention, a nucleotide analog or “tag” is incorporated duringamplification (e.g., a 5-(trifluoromethyl)deoxythymidine triphosphate)which has a different molecular weight than the unmodified base so as toimprove distinction of masses. Such tags are described in, for example,PCT WO97/33000, which is incorporated herein by reference in itsentirety. This further limits the number of possible base compositionsconsistent with any mass. For example, 5-(trifluoromethyl)deoxythymidinetriphosphate can be used in place of dTTP in a separate nucleic acidamplification reaction. Measurement of the mass shift between aconventional amplification product and the tagged product is used toquantitate the number of thymidine nucleotides in each of the singlestrands. Because the strands are complementary, the number of adenosinenucleotides in each strand is also determined.

In another amplification reaction, the number of G and C residues ineach strand is determined using, for example, the cytidine analog5-methylcytosine (5-meC) or propyne C. The combination of the A/Treaction and G/C reaction, followed by molecular weight determination,provides a unique base composition. This method is summarized in FIG. 4and Table 1.

TABLE 1 Total Total Total Base Base base base Double Single mass infoinfo comp. comp. strand strand this this other Top Bottom Mass tagsequence Sequence strand strand strand strand strand T*.massT*ACGT*ACGT* T*ACGT*ACGT* 3x 3T 3A 3T 3A (T* − T) = x AT*GCAT*GCA 2A 2T2C 2G 2G 2C AT*GCAT*GCA 2x 2T 2A C*.mass TAC*GTAC*GT TAC*GTAC*GT 2x 2C2G (C* − C) = y ATGC*ATGC*A ATGC*ATGC*A 2x 2C 2G

The mass tag phosphorothioate A (A*) was used to distinguish a Bacillusanthracis cluster. The B. anthracis (A₁₄G₉C₁₄T₉) had an average MW of14072.26, and the B. anthracis (A₁A*₁₃G₉C₁₄T₉) had an average molecularweight of 14281.11 and the phosphorothioate A had an average molecularweight of +16.06 as determined by ESI-TOF MS. The deconvoluted spectraare shown in FIG. 5.

In another example, assume the measured molecular masses of each strandare 30,000.115 Da and 31,000.115 Da respectively, and the measurednumber of dT and dA residues are (30,28) and (28,30). If the molecularmass is accurate to 100 ppm, there are 7 possible combinations of dG+dCpossible for each strand. However, if the measured molecular mass isaccurate to 10 ppm, there are only 2 combinations of dG+dC, and at 1 ppmaccuracy there is only one possible base composition for each strand.

Signals from the mass spectrometer may be input to a maximum-likelihooddetection and classification algorithm such as is widely used in radarsignal processing. The detection processing uses matched filtering ofBCS observed in mass-basecount space and allows for detection andsubtraction of signatures from known, harmless organisms, and fordetection of unknown bioagent threats. Comparison of newly observedbioagents to known bioagents is also possible, for estimation of threatlevel, by comparing their BCS to those of known organisms and to knownforms of pathogenicity enhancement, such as insertion of antibioticresistance genes or toxin genes.

Processing may end with a Bayesian classifier using log likelihoodratios developed from the observed signals and average backgroundlevels. The program emphasizes performance predictions culminating inprobability-of-detection versus probability-of-false-alarm plots forconditions involving complex backgrounds of naturally occurringorganisms and environmental contaminants. Matched filters consist of apriori expectations of signal values given the set of primers used foreach of the bioagents. A genomic sequence database (e.g. GenBank) isused to define the mass basecount matched filters. The database containsknown threat agents and benign background organisms. The latter is usedto estimate and subtract the signature produced by the backgroundorganisms. A maximum likelihood detection of known background organismsis implemented using matched filters and a running-sum estimate of thenoise covariance. Background signal strengths are estimated and usedalong with the matched filters to form signatures which are thensubtracted. the maximum likelihood process is applied to this “cleanedup” data in a similar manner employing matched filters for the organismsand a running-sum estimate of the noise-covariance for the cleaned updata.

F. Base Composition Signatures as Indices of Bioagent IdentifyingAmplicons

Although the molecular mass of amplification products obtained usingintelligent primers provides a means for identification of bioagents,conversion of molecular mass data to a base composition signature isuseful for certain analyses. As used herein, a “base compositionsignature” (BCS) is the exact base composition determined from themolecular mass of a bioagent identifying amplicon. In one embodiment, aBCS provides an index of a specific gene in a specific organism.

Base compositions, like sequences, vary slightly from isolate to isolatewithin species. It is possible to manage this diversity by building“base composition probability clouds” around the composition constraintsfor each species. This permits identification of organisms in a fashionsimilar to sequence analysis. A “pseudo four-dimensional plot” can beused to visualize the concept of base composition probability clouds(FIG. 18). Optimal primer design requires optimal choice of bioagentidentifying amplicons and maximizes the separation between the basecomposition signatures of individual bioagents. Areas where cloudsoverlap indicate regions that may result in a misclassification, aproblem which is overcome by selecting primers that provide informationfrom different bioagent identifying amplicons, ideally maximizing theseparation of base compositions. Thus, one aspect of the utility of ananalysis of base composition probability clouds is that it provides ameans for screening primer sets in order to avoid potentialmisclassifications of BCS and bioagent identity. Another aspect of theutility of base composition probability clouds is that they provide ameans for predicting the identity of a bioagent whose exact measured BCSwas not previously observed and/or indexed in a BCS database due toevolutionary transitions in its nucleic acid sequence.

It is important to note that, in contrast to probe-based techniques,mass spectrometry determination of base composition does not requireprior knowledge of the composition in order to make the measurement,only to interpret the results. In this regard, the present inventionprovides bioagent classifying information similar to DNA sequencing andphylogenetic analysis at a level sufficient to detect and identify agiven bioagent. Furthermore, the process of determination of apreviously unknown BCS for a given bioagent (for example, in a casewhere sequence information is unavailable) has downstream utility byproviding additional bioagent indexing information with which topopulate BCS databases. The process of future bioagent identification isthus greatly improved as more BCS indexes become available in the BCSdatabases.

Another embodiment of the present invention is a method of surveyingbioagent samples that enables detection and identification of allbacteria for which sequence information is available using a set oftwelve broad-range intelligent PCR primers. Six of the twelve primersare “broad range survey primers” herein defined as primers targeted tobroad divisions of bacteria (for example, the Bacillus/Clostridia groupor gamma-proteobacteria). The other six primers of the group of twelveprimers are “division-wide” primers herein defined as primers whichprovide more focused coverage and higher resolution. This method enablesidentification of nearly 100% of known bacteria at the species level. Afurther example of this embodiment of the present invention is a methodherein designated “survey/drill-down” wherein a subspeciescharacteristic for detected bioagents is obtained using additionalprimers. Examples of such a subspecies characteristic include but arenot limited to: antibiotic resistance, pathogenicity island, virulencefactor, strain type, sub-species type, and clade group. Using thesurvey/drill-down method, bioagent detection, confirmation and asubspecies characteristic can be provided within hours. Moreover, thesurvey/drill-down method can be focused to identify bioengineeringevents such as the insertion of a toxin gene into a bacterial speciesthat does not normally make the toxin.

G. Fields of Application of the Present Invention

The present methods allow extremely rapid and accurate detection andidentification of bioagents compared to existing methods. Furthermore,this rapid detection and identification is possible even when samplematerial is impure. The methods leverage ongoing biomedical research invirulence, pathogenicity, drug resistance and genome sequencing into amethod which provides greatly improved sensitivity, specificity andreliability compared to existing methods, with lower rates of falsepositives. Thus, the methods are useful in a wide variety of fields,including, but not limited to, those fields discussed below.

1. Forensics Methods

In other embodiments of the invention, the methods disclosed herein canbe used for forensics. As used herein, “forensics” is the study ofevidence discovered at a crime or accident scene and used in a court oflaw. “Forensic science” is any science used for the purposes of the law,in particular the criminal justice system, and therefore providesimpartial scientific evidence for use in the courts of law, and in acriminal investigation and trial. Forensic science is amultidisciplinary subject, drawing principally from chemistry andbiology, but also from physics, geology, psychology and social science,for example.

The process of human identification is a common objective of forensicsinvestigations. For example, there exists a need for rapididentification of humans wherein human remains and/or biological samplesare analyzed. Such remains or samples may be associated with war-relatedcasualties, aircraft crashes, and acts of terrorism, for example.Analysis of mtDNA enables a rule-in/rule-out identification process forpersons for whom DNA profiles from a maternal relative are available.Human identification by analysis of mtDNA can also be applied to humanremains and/or biological samples obtained from crime scenes.

Nucleic acid segments which provide enough variability to distinguisheach individual bioagent and whose molecular masses are amenable tomolecular mass determination are herein described as “bioagentidentifying amplicons.” The bioagent identifying amplicons used in thepresent invention for analysis of mitochondrial DNA are defined as“mitochondrial DNA identifying amplicons.”

Forensic scientists generally use two highly variable regions of humanmtDNA for analysis. These regions are designated “hypervariable regions1 and 2” (HVR1 and HVR2—which contain 341 and 267 base pairsrespectively). These hypervariable regions, or portions thereof, provideone non-limiting example of mitochondrial DNA identifying amplicons.

A mtDNA analysis begins when total genomic DNA is extracted frombiological material, such as a tooth, blood sample, or hair. Thepolymerase chain reaction (PCR) is then used to amplify, or create manycopies of, the two hypervariable portions of the non-coding region ofthe mtDNA molecule, using flanking primers. Care is taken to eliminatethe introduction of exogenous DNA during both the extraction andamplification steps via methods such as the use of pre-packaged sterileequipment and reagents, aerosol-resistant barrier pipette tips, gloves,masks, and lab coats, separation of pre- and post-amplification areas inthe lab using dedicated reagents for each, ultraviolet irradiation ofequipment, and autoclaving of tubes and reagent stocks. In casework,questioned samples are always processed before known samples and theyare processed in different laboratory rooms. When adequate amounts ofPCR product are amplified to provide all the necessary information aboutthe two hypervariable regions, sequencing reactions are performed. Thesechemical reactions use each PCR product as a template to create a newcomplementary strand of DNA in which some of the nucleotide residuesthat make up the DNA sequence are labeled with dye. The strands createdin this stage are then separated according to size by an automatedsequencing machine that uses a laser to “read” the sequence, or order,of the nucleotide bases. Where possible, the sequences of bothhypervariable regions are determined on both strands of thedouble-stranded DNA molecule, with sufficient redundancy to confirm thenucleotide substitutions that characterize that particular sample. Atleast two forensic analysts independently assemble the sequence and thencompare it to a standard, commonly used, reference sequence. The entireprocess is then repeated with a known sample, such as blood or salivacollected from a known individual. The sequences from both samples,about 780 bases long each, are compared to determine if they match. Theanalysts assess the results of the analysis and determine if anyportions of it need to be repeated. Finally, in the event of aninclusion or match, the SWGDAM mtDNA database, which is maintained bythe FBI, is searched for the mitochondrial sequence that has beenobserved for the samples. The analysts can then report the number ofobservations of this type based on the nucleotide positions that havebeen read. A written report can be provided to the submitting agency.

2. Determination and Quantitation of Mitochondrial DNA Heteroplasmy

In one embodiment of the present invention, the methods disclosed hereinfor rapid identification of bioagents using base composition signaturesare employed for analysis of human mtDNA. The advantages provided bythis embodiment of the present invention include, but are not limitedto, efficiency of mass determination of amplicons over sequencedetermination, and the ability to resolve mixtures of mtDNA ampliconsarising from heteroplasmy. Such mixtures invariably cause sequencingfailures.

In another embodiment of the present invention, the methods disclosedherein for mtDNA analysis can be used to identify the presence ofheteroplasmic variants and to determine their relative abundances. Asused herein, “mitochondrial diseases” are defined as diseases arisingfrom defects in mitochondrial function which often arise as a result ofmutations and heteroplasmy. If the defect is in the mitochondrial ratherthan the nuclear genome unusual patterns of inheritance can be observed.This embodiment can be used to determine rates of naturally occurringmutations contributing to heteroplasmy and to predict the onset ofmitochondrial diseases arising from heteroplasmy. Examples ofmitochondrial diseases include, but are not limited to: Alpers Disease,Barth syndrome, Beta-oxidation Defects, Carnitine-Acyl-CarnitineDeficiency, Carnitine Deficiency, Co-Enzyme Q10 Deficiency, Complex IDeficiency, Complex II Deficiency, Complex III Deficiency, Complex IVDeficiency, Complex V Deficiency, COX Deficiency, CPEO, CPT IDeficiency, CPT II Deficiency, Glutaric Aciduria Type II, KSS, LacticAcidosis, LCAD, LCHAD, Leigh Disease or Syndrome, LHON, Lethal InfantileCardiomyopathy, Luft Disease, MAD, MCA, MELAS, MERRF, MitochondrialCytopathy, Mitochondrial DNA Depletion, Mitochondrial Encephalopathy,Mitochondrial Myopathy, MNGIE, NARP, Pearson Syndrome, PyruvateCarboxylase Deficiency, Pyruvate Dehydrogenase Deficiency, RespiratoryChain, SCAD, SCHAD, VLCAD, and the like(www.umdf.org/mitodisease/descriptions.html).

In another embodiment of the present invention, the methods disclosedherein can be used to rapidly determine the identity of a fungus or aprotist by analysis of its mtDNA.

In addition, epidemiologists, for example, can use the present methodsto determine the geographic origin of a particular strain of a protistor fungus. For example, a particular strain of bacteria or virus mayhave a sequence difference that is associated with a particular area ofa country or the world and identification of such a sequence differencecan lead to the identification of the geographic origin andepidemiological tracking of the spread of the particular disease,disorder or condition associated with the detected protist or fungus. Inaddition, carriers of particular DNA or diseases, such as mammals,non-mammals, birds, insects, and plants, can be tracked by screeningtheir mtDNA. Diseases, such as malaria, can be tracked by screening themtDNA of commensals such as mosquitoes.

The present method can also be used to detect single nucleotidepolymorphisms (SNPs), or multiple nucleotide polymorphisms, rapidly andaccurately. A SNP is defined as a single base pair site in the genomethat is different from one individual to another. The difference can beexpressed either as a deletion, an insertion or a substitution, and isfrequently linked to a disease state. Because they occur every 100-1000base pairs, SNPs are the most frequently bound type of genetic marker inthe human genome.

For example, sickle cell anemia results from an A-T transition, whichencodes a valine rather than a glutamic acid residue. Oligonucleotideprimers may be designed such that they bind to sequences that flank aSNP site, followed by nucleotide amplification and mass determination ofthe amplified product. Because the molecular masses of the resultingproduct from an individual who does not have sickle cell anemia isdifferent from that of the product from an individual who has thedisease, the method can be used to distinguish the two individuals.Thus, the method can be used to detect any known SNP in an individualand thus diagnose or determine increased susceptibility to a disease orcondition.

In one embodiment, blood is drawn from an individual and peripheralblood mononuclear cells (PBMC) are isolated and simultaneously tested,preferably in a high-throughput screening method, for one or more SNPsusing appropriate primers based on the known sequences which flank theSNP region. The National Center for Biotechnology Information maintainsa publicly available database of SNPs on the world wide web of theInternet at, for example, “ncbi.nlm.nih.gov/SNP/.”

The method of the present invention can also be used for blood typing.The gene encoding A, B or O blood type can differ by four singlenucleotide polymorphisms. If the gene contains the sequenceCGTGGTGACCCTT (SEQ ID NO:5), antigen A results. If the gene contains thesequence CGTCGTCACCGCTA (SEQ ID NO:6) antigen B results. If the genecontains the sequence CGTGGT-ACCCCTT (SEQ ID NO:7), blood group Oresults (“-” indicates a deletion). These sequences can be distinguishedby designing a single primer pair which flanks these regions, followedby amplification and mass determination.

While the present invention has been described with specificity inaccordance with certain of its embodiments, the following examples serveonly to illustrate the invention and are not intended to limit the same.

EXAMPLES Example 1 Nucleic Acid Isolation and PCR

In one embodiment, nucleic acid is isolated from the organisms andamplified by PCR using standard methods prior to BCS determination bymass spectrometry. Nucleic acid is isolated, for example, by detergentlysis of bacterial cells, centrifugation and ethanol precipitation.Nucleic acid isolation methods are described in, for example, CurrentProtocols in Molecular Biology (Ausubel et al.) and Molecular Cloning; ALaboratory Manual (Sambrook et al.). The nucleic acid is then amplifiedusing standard methodology, such as PCR, with primers which bind toconserved regions of the nucleic acid which contain an interveningvariable sequence as described below.

General Genomic DNA Sample Prep Protocol: Raw samples are filtered usingSupor-200 0.2 μm membrane syringe filters (VWR International). Samplesare transferred to 1.5 ml eppendorf tubes pre-filled with 0.45 g of 0.7mm Zirconia beads followed by the addition of 350 μl of ATL buffer(Qiagen, Valencia, Calif.). The samples are subjected to bead beatingfor 10 minutes at a frequency of 19 l/s in a Retsch Vibration Mill(Retsch). After centrifugation, samples are transferred to an S-blockplate (Qiagen) and DNA isolation is completed with a BioRobot 8000nucleic acid isolation robot (Qiagen).

Swab Sample Protocol. Allegiance S/P brand culture swabs andcollection/transport system are used to collect samples. After drying,swabs are placed in 17×100 mm culture tubes (VWR International) and thegenomic nucleic acid isolation is carried out automatically with aQiagen Mdx robot and the Qiagen QIAamp DNA Blood BioRobot Mdx genomicpreparation kit (Qiagen, Valencia, Calif.).

Example 2 Mass Spectrometry

FTICR Instrumentation: The FTICR instrument is based on a 7 teslaactively shielded superconducting magnet and modified Bruker DaltonicsApex II 70e ion optics and vacuum chamber. The spectrometer isinterfaced to a LEAP PAL autosampler and a custom fluidics controlsystem for high throughput screening applications. Samples are analyzeddirectly from 96-well or 384-well microtiter plates at a rate of about 1sample/minute. The Bruker data-acquisition platform is supplemented witha lab-built ancillary NT datastation which controls the autosampler andcontains an arbitrary waveform generator capable of generating complexrf-excite waveforms (frequency sweeps, filtered noise, stored waveforminverse Fourier transform (SWIFT), etc.) for sophisticated tandem MSexperiments. For oligonucleotides in the 20-30-mer regime typicalperformance characteristics include mass resolving power in excess of100,000 (FWHM), low ppm mass measurement errors, and an operable m/zrange between 50 and 5000 m/z.

Modified ESI Source. In sample-limited analyses, analyte solutions aredelivered at 150 mL/minute to a 30 mm i.d. fused-silica ESI emittermounted on a 3-D micromanipulator. The ESI ion optics consists of aheated metal capillary, an rf-only hexapole, a skimmer cone, and anauxiliary gate electrode. The 6.2 cm rf-only hexapole is comprised of 1mm diameter rods and is operated at a voltage of 380 Vpp at a frequencyof 5 MHz. A lab-built electro-mechanical shutter can be employed toprevent the electrospray plume from entering the inlet capillary unlesstriggered to the “open” position via a TTL pulse from the data station.When in the “closed” position, a stable electrospray plume is maintainedbetween the ESI emitter and the face of the shutter. The back face ofthe shutter arm contains an elastomeric seal that can be positioned toform a vacuum seal with the inlet capillary. When the seal is removed, a1 mm gap between the shutter blade and the capillary inlet allowsconstant pressure in the external ion reservoir regardless of whetherthe shutter is in the open or closed position. When the shutter istriggered, a “time slice” of ions is allowed to enter the inletcapillary and is subsequently accumulated in the external ion reservoir.The rapid response time of the ion shutter (<25 ms) providesreproducible, user defined intervals during which ions can be injectedinto and accumulated in the external ion reservoir.

Apparatus for Infrared Multiphoton Dissociation. A 25 watt CW CO₂ laseroperating at 10.6 μm has been interfaced to the spectrometer to enableinfrared multiphoton dissociation (IRMPD) for oligonucleotide sequencingand other tandem MS applications. An aluminum optical bench ispositioned approximately 1.5 m from the actively shieldedsuperconducting magnet such that the laser beam is aligned with thecentral axis of the magnet. Using standard IR-compatible mirrors andkinematic mirror mounts, the unfocused 3 mm laser beam is aligned totraverse directly through the 3.5 mm holes in the trapping electrodes ofthe FTICR trapped ion cell and longitudinally traverse the hexapoleregion of the external ion guide finally impinging on the skimmer cone.This scheme allows IRMPD to be conducted in an m/z selective manner inthe trapped ion cell (e.g. following a SWIFT isolation of the species ofinterest), or in a broadband mode in the high pressure region of theexternal ion reservoir where collisions with neutral molecules stabilizeIRMPD-generated metastable fragment ions resulting in increased fragmention yield and sequence coverage.

Example 3 Identification of Bioagents

Table 2 shows a small cross section of a database of calculatedmolecular masses for over 9 primer sets and approximately 30 organisms.The primer sets were derived from rRNA alignment. Examples of regionsfrom rRNA consensus alignments are shown in FIGS. 1A-1C. Lines witharrows are examples of regions to which intelligent primer pairs for PCRare designed. The primer pairs are >95% conserved in the bacterialsequence database (currently over 10,000 organisms). The interveningregions are variable in length and/or composition, thus providing thebase composition “signature” (BCS) for each organism. Primer pairs werechosen so the total length of the amplified region is less than about80-90 nucleotides. The label for each primer pair represents thestarting and ending base number of the amplified region on the consensusdiagram.

Included in the short bacterial database cross-section in Table 2 aremany well known pathogens/biowarfare agents (shown in bold/red typeface)such as Bacillus anthracis or Yersinia pestis as well as some of thebacterial organisms found commonly in the natural environment such asStreptomyces. Even closely related organisms can be distinguished fromeach other by the appropriate choice of primers. For instance, two lowG+C organisms, Bacillus anthracis and Staph aureus, can be distinguishedfrom each other by using the primer pair defined by 16S_(—)1337 or23S_(—)855 (ΔM of 4 Da).

TABLE 2 Cross Section Of A Database Of Calculated Molecular Masses¹Primer Regions Bug Name 16S_971 16S_1100 16S_1337 16S_1294 16S_122823S_1021 23S_855 23S_193 23S_115 Acinetobacter calcoaceticus 55619.155004 28446.7 35854.9 51295.4 30299 42654 39557.5 54999

55005 54388 28448 35238 51296 30295 42651 39560 56850 Bacillus cereus55622.1 54387.9 28447.6 35854.9 51296.4 30295 42651 39560.5 56850.3Bordetella bronchiseptica 56857.3 51300.4 28446.7 35857.9 51307.4 3029942653 39559.5 51920.5 Borrelia burgdorferi 56231.2 55621.1 28440.735852.9 51295.4 30297 42029.9 38941.4 52524.6

58098 55011 28448 35854 50683 Campylobacter jejuni 58088.5 54386.929061.8 35856.9 50674.3 30294 42032.9 39558.5 45732.5

55000 55007 29063 35855 50676 30295 42036 38941 56230

55006 53767 28445 35855 51291 30300 42656 39562 54999 Clostridiumdifficile 56855.3 54386.9 28444.7 35853.9 51296.4 30294 41417.8 39556.555612.2 Enterococcus faecalis 55620.1 54387.9 28447.6 35858.9 51296.430297 42652 39559.5 56849.3

55622 55009 28445 35857 51301 30301 42656 39562 54999

53769 54385 28445 35856 51298 Haemophilus influenzae 55620.1 5500628444.7 35855.9 51298.4 30298 42656 39560.5 55613.1 Klebsiellapneumoniae 55622.1 55008 28442.7 35856.9 51297.4 30300 42655 39562.555000

55618 55626 28446 35857 51303 Mycobacterium avium 54390.9 55631.129064.8 35858.9 51915.5 30298 42656 38942.4 56241.2 Mycobacterium leprae54389.9 55629.1 29064.8 35860.9 51917.5 30298 42656 39559.5 56240.2Mycobacterium tuberculosis 54390.9 55629.1 29064.8 35860.9 51301.4 3029942656 39560.5 56243.2 Mycoplasma genitalium 53143.7 45115.4 29061.835854.9 50671.3 30294 43264.1 39558.5 56842.4 Mycoplasma pneumoniae53143.7 45118.4 29061.8 35854.9 50673.3 30294 43264.1 39559.5 56843.4Neisseria gonorrhoeae 55627.1 54389.9 28445.7 35855.9 51302.4 3030042649 39561.5 55000

55623 55010 28443 35858 51301 30298 43272 39558 55619

58093 55621 28448 35853 50677 30293 42650 39559 53139

58094 55623 28448 35853 50679 30293 42648 39559 53755

55622 55005 28445 35857 51301 30301 42658

55623 55009 28444 35857 51301 Staphylococcus aureus 56854.3 54386.928443.7 35852.9 51294.4 30298 42655 39559.5 57466.4 Streptomyces 54389.959341.6 29063.8 35858.9 51300.4 39563.5 56864.3 Treponema pallidum56245.2 55631.1 28445.7 35851.9 51297.4 30299 42034.9 38939.4 57473.4

55625 55626 28443 35857 52536 29063 30303 35241 50675 Vibrioparahaemolyticus 54384.9 55626.1 28444.7 34620.7 50064.2

55620 55626 28443 35857 51299 ¹Molecular mass distribution of PCRamplified regions for a selection of organisms (rows) across variousprimer pairs (columns). Pathogens are shown in bold. Empty cellsindicate presently incomplete or missing data.

FIG. 6 shows the use of ESI-FT-ICR MS for measurement of exact mass. Thespectra from 46mer PCR products originating at position 1337 of the 16SrRNA from S. aureus (upper) and B. anthracis (lower) are shown. Thesedata are from the region of the spectrum containing signals from the[M-8H+]⁸⁻ charge states of the respective 5′-3′ strands. The two strandsdiffer by two (AT→CG) substitutions, and have measured masses of14206.396 and 14208.373+0.010 Da, respectively. The possible basecompositions derived from the masses of the forward and reverse strandsfor the B. anthracis products are listed in Table 3.

TABLE 3 Possible base composition for B. anthracis products Calc. MassError Base Comp. 14208.2935 0.079520 A1 G17 C10 T18 14208.3160 0.056980A1 G20 C15 T10 14208.3386 0.034440 A1 G23 C20 T2 14208.3074 0.065560 A6G11 C3 T26 14208.3300 0.043020 A6 G14 C8 T18 14208.3525 0.020480 A6 G17C13 T10 14208.3751 0.002060 A6 G20 C18 T2 14208.3439 0.029060 A11 G8 C1T26 14208.3665 0.006520 A11 G11 C6 T18 14208.3890 0.016020 A11 G14 C11T10 14208.4116 0.038560 A11 G17 C16 T2 14208.4030 0.029980 A16 G8 C4 T1814208.4255 0.052520 A16 G11 C9 T10 14208.4481 0.075060 A16 G14 C14 T214208.4395 0.066480 A21 G5 C2 T18 14208.4620 0.089020 A21 G8 C7 T1014079.2624 0.080600 A0 G14 C13 T19 14079.2849 0.058060 A0 G17 C18 T1114079.3075 0.035520 A0 G20 C23 T3 14079.2538 0.089180 A5 G5 C1 T3514079.2764 0.066640 A5 G8 C6 T27 14079.2989 0.044100 A5 G11 C11 T1914079.3214 0.021560 A5 G14 C16 T11 14079.3440 0.000980 A5 G17 C21 T314079.3129 0.030140 A10 G5 C4 T27 14079.3354 0.007600 A10 G8 C9 T1914079.3579 0.014940 A10 G11 C14 T11 14079.3805 0.037480 A10 G14 C19 T314079.3494 0.006360 A15 G2 C2 T27 14079.3719 0.028900 A15 G5 C7 T1914079.3944 0.051440 A15 G8 C12 T11 14079.4170 0.073980 A15 G11 C17 T314079.4084 0.065400 A20 G2 C5 T19 14079.4309 0.087940 A20 G5 C10 T13Among the 16 compositions for the forward strand and the 18 compositionsfor the reverse strand that were calculated, only one pair (shown inbold) are complementary, corresponding to the actual base compositionsof the B. anthracis PCR products.

Example 4 BCS of Region from Bacillus anthracis and Bacillus cereus

A conserved Bacillus region from B. anthracis (A₁₄G₉C₁₄T₉) and B. cereus(A₁₅G₉C₁₃T₉) having a C to A base change was synthesized and subjectedto ESI-TOF MS. The results are shown in FIG. 7 in which the two regionsare clearly distinguished using the method of the present invention(MW=14072.26 vs. 14096.29).

Example 5 Identification of Additional Bioagents

In other examples of the present invention, the pathogen Vibrio choleracan be distinguished from Vibrio parahemolyticus with ΔM>600 Da usingone of three 16S primer sets shown in Table 2 (16S_(—)971, 16S_(—)1228or 16S_(—)1294) as shown in Table 4. The two mycoplasma species in thelist (M. genitalium and M. pneumoniae) can also be distinguished fromeach other, as can the three mycobacteriae. While the direct massmeasurements of amplified products can identify and distinguish a largenumber of organisms, measurement of the base composition signatureprovides dramatically enhanced resolving power for closely relatedorganisms. In cases such as Bacillus anthracis and Bacillus cereus thatare virtually indistinguishable from each other based solely on massdifferences, compositional analysis or fragmentation patterns are usedto resolve the differences. The single base difference between the twoorganisms yields different fragmentation patterns, and despite thepresence of the ambiguous/unidentified base N at position 20 in B.anthracis, the two organisms can be identified.

Tables 4a-b show examples of primer pairs from Table 1 which distinguishpathogens from background.

TABLE 4a Organism name 23S_855 16S_1337 23S_1021 Bacillus anthracis42650.98 28447.65 30294.98 Staphylococcus aureus 42654.97 28443.6730297.96

TABLE 4b Organism name 16S_971 16S_1294 16S_1228 Vibrio cholerae55625.09 35856.87 52535.59 Vibrio parahaemolyticus 54384.91 34620.6750064.19

Table 5 shows the expected molecular weight and base composition ofregion 16S_(—)1100-188 in Mycobacterium avium and Streptomyces sp.

TABLE 5 Molecular Region Organism name Length weight Base comp.16S_1100-1188 Mycobacterium avium 82 25624.1728 A₁₆G₃₂C₁₈T₁₆16S_1100-1188 Streptomyces sp. 96 29904.871 A₁₇G₃₈C₂₇T₁₄

Table 6 shows base composition (single strand) results for16S_(—)1100-1188 primer amplification reactions different species ofbacteria. Species which are repeated in the table (e.g., Clostridiumbotulinum) are different strains which have different base compositionsin the 16S_(—)1100-1188 region.

TABLE 6 Organism name Base comp. Mycobacterium avium A₁₆G₃₂C₁₈T₁₆Streptomyces sp. A₁₇G₃₈C₂₇T₁₄ Ureaplasma urealyticum A₁₈G₃₀C₁₇T₁₇Streptomyces sp. A₁₉G₃₆C₂₄T₁₈ Mycobacterium leprae A₂₀G₃₂C₂₂T₁₆

A ₂₀ G ₃₃ C ₂₁ T ₁₆

A ₂₀ G ₃₃ C ₂₁ T ₁₆ Fusobacterium necroforum A₂₁G₂₆C₂₂T₁₈ Listeriamonocytogenes A₂₁G₂₇C₁₉T₁₉ Clostridium botulinum A₂₁G₂₇C₁₉T₂₁ Neisseriagonorrhoeae A₂₁G₂₈C₂₁T₁₈ Bartonella quintana A₂₁G₃₀C₂₂T₁₆ Enterococcusfaecalis A₂₂G₂₇C₂₀T₁₉ Bacillus megaterium A₂₂G₂₈C₂₀T₁₈ Bacillus subtilisA₂₂G₂₈C₂₁T₁₇ Pseudomonas aeruginosa A₂₂G₂₉C₂₃T₁₅ Legionella pneumophilaA₂₂G₃₂C₂₀T₁₆ Mycoplasma pneumoniae A₂₃G₂₀C₁₄T₁₆ Clostridium botulinumA₂₃G₂₆C₂₀T₁₉ Enterococcus faecium A₂₃G₂₆C₂₁T₁₈ Acinetobacter calcoacetiA₂₃G₂₆C₂₁T₁₉

A ₂₃ G ₂₆ C ₂₄ T ₁₅

A ₂₃ G ₂₆ C ₂₄ T ₁₅ Clostridium perfringens A₂₃G₂₇C₁₉T₁₉

A ₂₃ G ₂₇ C ₂₀ T ₁₈

A ₂₃ G ₂₇ C ₂₀ T ₁₈

A ₂₃ G ₂₇ C ₂₀ T ₁₈ Aeromonas hydrophila A ₂₃ G ₂₉ C ₂₁ T ₁₆ Escherichiacoli A ₂₃ G ₂₉ C ₂₁ T ₁₆ Pseudomonas putida A₂₃G₂₉C₂₁T₁₇

A ₂₃ G ₂₉ C ₂₂ T ₁₅

A ₂₃ G ₂₉ C ₂₂ T ₁₅ Vibrio cholerae A₂₃G₃₀C₂₁T₁₆

A ₂₃ G ₃₁ C ₂₁ T ₁₅

A ₂₃ G ₃₁ C ₂₁ T ₁₅ Mycoplasma genitalium A₂₄G₁₉C₁₂T₁₈ Clostridiumbotulinum A₂₄G₂₅C₁₈T₂₀ Bordetella bronchiseptica A₂₄G₂₆C₁₉T₁₄Francisella tularensis A₂₄G₂₆C₁₉T₁₉

A ₂₄ G ₂₆ C ₂₀ T ₁₈

A ₂₄ G ₂₆ C ₂₀ T ₁₈

A ₂₄ G ₂₆ C ₂₀ T ₁₈ Helicobacter pylori A₂₄G₂₆C₂₀T₁₉ Helicobacter pyloriA₂₄G₂₆C₂₁T₁₈ Moraxella catarrhalis A₂₄G₂₆C₂₃T₁₆ Haemophilus influenzaeRd A₂₄G₂₈C₂₀T₁₇

A ₂₄ G ₂₈ C ₂₁ T ₁₆

A ₂₄ G ₂₈ C ₂₁ T ₁₆

 AR39 A ₂₄ G ₂₈ C ₂₁ T ₁₆ Pseudomonas putida A₂₄G₂₉C₂₁T₁₆

A ₂₄ G ₃₀ C ₂₁ T ₁₅

A ₂₄ G ₃₀ C ₂₁ T ₁₅

A ₂₄ G ₃₀ C ₂₁ T ₁₅ Clostridium botulinum A₂₅G₂₄C₁₈T₂₁ Clostridiumtetani A₂₅G₂₅C₁₈T₂₀ Francisella tularensis A₂₅G₂₅C₁₉T₁₉ Acinetobactercalcoacetic A₂₅G₂₆C₂₀T₁₉ Bacteriodes fragilis A₂₅G₂₇C₁₆T₂₂ Chlamydophilapsittaci A₂₅G₂₇C₂₁T₁₆ Borrelia burgdorferi A₂₅G₂₉C₁₇T₁₉ Streptobacillusmonilifor A₂₆G₂₆C₂₀T₁₆ Rickettsia prowazekii A₂₆G₂₈C₁₈T₁₈ Rickettsiarickettsii A₂₆G₂₈C₂₀T₁₆ Mycoplasma mycoides A₂₈G₂₃C₁₆T₂₀

The same organism having different base compositions are differentstrains. Groups of organisms which are highlighted or in italics havethe same base compositions in the amplified region. Some of theseorganisms can be distinguished using multiple primers. For example,Bacillus anthracis can be distinguished from Bacillus cereus andBacillus thuringiensis using the primer 16S_(—)971-1062 (Table 7). Otherprimer pairs which produce unique base composition signatures are shownin Table 6 (bold). Clusters containing very similar threat andubiquitous non-threat organisms (e.g. anthracis cluster) aredistinguished at high resolution with focused sets of primer pairs. Theknown biowarfare agents in Table 6 are Bacillus anthracis, Yersiniapestis, Francisella tularensis and Rickettsia prowazekii.

TABLE 7 Organism 16S_971-1062 16S_1228-1310 16S_1100-1188 Aeromonashydrophila A₂₁G₂₉C₂₂T₂₀ A₂₂G₂₇C₂₁T₁₃ A₂₃G₃₁C₂₁T₁₅ Aeromonas salmonicidaA₂₁G₂₉C₂₂T₂₀ A₂₂G₂₇C₂₁T₁₃ A₂₃G₃₁C₂₁T₁₅ Bacillus anthracis A ₂₁G₂₇C₂₂T₂₂A₂₄G₂₂C₁₉T₁₈ A₂₃G₂₇C₂₀T₁₈ Bacillus cereus A₂₂G₂₇C₂₂T₂₂ A₂₄G₂₂C₁₉T₁₈A₂₃G₂₇C₂₀T₁₈ Bacillus thuringiensis A₂₂G₂₇C₂₁T₂₂ A₂₄G₂₂C₁₉T₁₈A₂₃G₂₇C₂₀T₁₈ Chlamydia trachomatis A ₂₂G₂₆C₂₀T₂₃ A ₂₄G₂₃C₁₉T₁₆A₂₄G₂₈C₂₁T₁₆ Chlamydia pneumoniae AR39 A₂₆G₂₃C₂₀T₂₂ A₂₆G₂₂C₁₆T₁₈A₂₄G₂₈C₂₁T₁₆ Leptospira borgpetersenii A₂₂G₂₆C₂₀T₂₁ A₂₂G₂₅C₂₁T₁₅A₂₃G₂₆C₂₄T₁₅ Leptospira interrogans A₂₂G₂₆C₂₀T₂₁ A₂₂G₂₅C₂₁T₁₅A₂₃G₂₆C₂₄T₁₅ Mycoplasma genitalium A₂₈G₂₃C₁₅T₂₂ A ₃₀G₁₈C₁₅T₁₉ A₂₄G₁₉C₁₂T₁₈ Mycoplasma pneumoniae A₂₈G₂₃C₁₅T₂₂ A ₂₇G₁₉C₁₆T₂₀ A₂₃G₂₀C₁₄T₁₆ Escherichia coli A ₂₂G₂₈C₂₀T₂₂ A₂₄G₂₅C₂₁T₁₃ A₂₃G₂₉C₂₂T₁₅Shigella dysenteriae A ₂₂G₂₈C₂₁T₂₁ A₂₄G₂₅C₂₁T₁₃ A₂₃G₂₉C₂₂T₁₅ Proteusvulgaris A ₂₃G₂₆C₂₂T₂₁ A ₂₆G₂₄C₁₉T₁₄ A₂₄G₃₀C₂₁T₁₅ Yersinia pestisA₂₄G₂₅C₂₁T₂₂ A₂₅G₂₄C₂₀T₁₄ A₂₄G₃₀C₂₁T₁₅ Yersinia pseudotuberculosisA₂₄G₂₅C₂₁T₂₂ A₂₅G₂₄C₂₀T₁₄ A₂₄G₃₀C₂₁T₁₅ Francisella tularensis A₂₀G₂₅C₂₁T₂₃ A ₂₃G₂₆C₁₇T₁₇ A ₂₄G₂₆C₁₉T₁₉ Rickettsia prowazekii A₂₁G₂₆C₂₄T₂₅ A ₂₄G₂₃C₁₆T₁₉ A ₂₆G₂₈C₁₈T₁₈ Rickettsia rickettsii A₂₁G₂₆C₂₅T₂₄ A ₂₄G₂₄C₁₇T₁₇ A ₂₆G₂₈C₂₀T₁₆

The sequence of B. anthracis and B. cereus in region 16S_(—)971 is shownbelow. Shown in bold is the single base difference between the twospecies which can be detected using the methods of the presentinvention. B. anthracis has an ambiguous base at position 20.

B.anthracis_16S_971 (SEQ ID NO: 1)GCGAAGAACCUUACCAGGUNUUGACAUCCUCUGACAACCCUAGAGAUAGGGCUUCUCCUUCGGGAGCAGAGUGACAGGUGGUGCAUGGUU B.cereus_16S_971 (SEQ ID NO:2)GCGAAGAACCUUACCAGGUCUUGACAUCCUCUGAAAACCCUAGAGAUAGGGCUUCUCCUUCGGGAGCAGAGUGACAGGUGGUGCAUGGUU

Example 6 ESI-TOF MS of sspE 56-mer Plus Calibrant

The mass measurement accuracy that can be obtained using an internalmass standard in the ESI-MS study of PCR products is shown in FIG. 8.The mass standard was a 20-mer phosphorothioate oligonucleotide added toa solution containing a 56-mer PCR product from the B. anthracis sporecoat protein sspE. The mass of the expected PCR product distinguishes B.anthracis from other species of Bacillus such as B. thuringiensis and B.cereus.

Example 7 B. anthracis ESI-TOF Synthetic 16S_(—)1228 Duplex

An ESI-TOF MS spectrum was obtained from an aqueous solution containing5 μM each of synthetic analogs of the expected forward and reverse PCRproducts from the nucleotide 1228 region of the B. anthracis 16S rRNAgene. The results (FIG. 9) show that the molecular weights of theforward and reverse strands can be accurately determined and easilydistinguish the two strands. The [M-21H⁺]²¹⁻ and [M-20H⁺]²⁰⁻ chargestates are shown.

Example 8 ESI-FTICR-MS of Synthetic B. anthracis 16S_(—)1337 46 BasePair Duplex

An ESI-FTICR-MS spectrum was obtained from an aqueous solutioncontaining 5 μM each of synthetic analogs of the expected forward andreverse PCR products from the nucleotide 1337 region of the B. anthracis16S rRNA gene. The results (FIG. 10) show that the molecular weights ofthe strands can be distinguished by this method. The [M-16H⁺]¹⁶⁻ through[M-10H⁺]¹⁰⁻ charge states are shown. The insert highlights theresolution that can be realized on the FTICR-MS instrument, which allowsthe charge state of the ion to be determined from the mass differencebetween peaks differing by a single 13C substitution.

Example 9 ESI-TOF MS of 56-mer Oligonucleotide from saspB Gene of B.anthracis with Internal Mass Standard

ESI-TOF MS spectra were obtained on a synthetic 56-mer oligonucleotide(5 μM) from the saspB gene of B. anthracis containing an internal massstandard at an ESI of 1.7 μL/min as a function of sample consumption.The results (FIG. 11) show that the signal to noise is improved as morescans are summed, and that the standard and the product are visibleafter only 100 scans.

Example 10 ESI-TOF MS of an Internal Standard with Tributylammonium(TBA)-trifluoroacetate (TFA) Buffer

An ESI-TOF-MS spectrum of a 20-mer phosphorothioate mass standard wasobtained following addition of 5 mM TBA-TFA buffer to the solution. Thisbuffer strips charge from the oligonucleotide and shifts the mostabundant charge state from [M-8H⁺]⁸⁻ to [M-3H⁺]³⁻ (FIG. 12).

Example 11 Master Database Comparison

The molecular masses obtained through Examples 1-10 are compared tomolecular masses of known bioagents stored in a master database toobtain a high probability matching molecular mass.

Example 12 Master Data Base Interrogation Over the Internet

The same procedure as in Example 11 is followed except that the localcomputer did not store the Master database. The Master database isinterrogated over an internet connection, searching for a molecular massmatch.

Example 13 Master Database Updating

The same procedure as in example 11 is followed except the localcomputer is connected to the internet and has the ability to store amaster database locally. The local computer system periodically, or atthe user's discretion, interrogates the Master database, synchronizingthe local master database with the global Master database. This providesthe current molecular mass information to both the local database aswell as to the global Master database. This further provides more of aglobalized knowledge base.

Example 14 Global Database Updating

The same procedure as in example 13 is followed except there arenumerous such local stations throughout the world. The synchronizationof each database adds to the diversity of information and diversity ofthe molecular masses of known bioagents.

Example 15 Biochemical Processing of Large Amplification Products forAnalysis by Mass Spectrometry

In the example illustrated in FIG. 18, a primer pair which amplifies a986 bp region of the 16S ribosomal gene in E. coli (K12) was digestedwith a mixture of 4 restriction enzymes: BstN1, BsmF1, Bfa1, and Nco1.FIG. 18( a) illustrates the complexity of the resulting ESI-FTICR massspectrum which contains multiple charge states of multiple restrictionfragments. Upon mass deconvolution to neutral mass, the spectrum issignificantly simplified and discrete oligonucleotide pairs are evident(FIG. 18( b). When base compositions are derived from the masses of therestriction fragments, perfect agreement is observed for the knownsequence of nucleotides 1-856 (FIG. 18( c); the batch of Nco1 enzymeused in this experiment was inactive and resulted in a missed cleavagesite and a 197-mer fragment went undetected as it is outside the massrange of the mass spectrometer under the conditions employed.Interestingly however, both a forward and reverse strand were detectedfor each fragment measured (solid and dotted lines in, respectively)within 2 ppm of the predicted molecular weights resulting in unambiguousdetermination of the base composition of 788 nucleotides of the 985nucleotides in the amplicon. The coverage map offers redundant coverageas both 5′ to 3′ and 3′ to 5′ fragments are detected for fragmentscovering the first 856 nucleotides of the amplicon.

This approach is in many ways analogous to those widely used in MS-basedproteomics studies in which large intact proteins are digested withtrypsin, or other proteolytic enzyme(s), and the identity of the proteinis derived by comparing the measured masses of the tryptic peptides withtheoretical digests. A unique feature of this approach is that theprecise mass measurements of the complementary strands of each digestproduct allow one to derive a de novo base composition for eachfragment, which can in turn be “stitched together” to derive a completebase composition for the larger amplicon. An important distinctionbetween this approach and a gel-based restriction mapping strategy isthat, in addition to determination of the length of each fragment, anunambiguous base composition of each restriction fragment is derived.Thus, a single base substitution within a fragment (which would not beresolved on a gel) is readily observed using this approach. Because thisstudy was performed on a 7 Tesla ESI-FTICR mass spectrometer, betterthan 2 ppm mass measurement accuracy was obtained for all fragments.Interestingly, calculation of the mass measurement accuracy required toderive unambiguous base compositions from the complementary fragmentsindicates that the highest mass measurement accuracy actually requiredis only 15 ppm for the 139 bp fragment (nucleotides 525-663). Most ofthe fragments were in the 50-70 bp size-range which would require massaccuracy of only ˜50 ppm for unambiguous base composition determination.This level of performance is achievable on other more compact, lessexpensive MS platforms such as the ESI-TOF suggesting that the methodsdeveloped here could be widely deployed in a variety of diagnostic andhuman forensic arenas.

This example illustrates an alternative approach to derive basecompositions from larger PCR products. Because the amplicons of interestcover many strain variants, for some of which complete sequences are notknown, each amplicon can be digested under several different enzymaticconditions to ensure that a diagnostically informative region of theamplicon is not obscured by a “blind spot” which arises from a mutationin a restriction site. The extent of redundancy required to confidentlymap the base composition of amplicons from different markers, anddetermine which set of restriction enzymes should be employed and howthey are most effectively used as mixtures can be determined. Theseparameters will be dictated by the extent to which the area of interestis conserved across the amplified region, the compatibility of thevarious restriction enzymes with respect to digestion protocol (buffer,temperature, time) and the degree of coverage required to discriminateone amplicon from another.

Example 16 Analysis of 10 Human Blood Mitochondrial DNA Samples Providedby the FBI

Ten different samples of human DNA provided by the FBI were subjected torapid mtDNA analysis by the method of the present invention. Intelligentprimers (SEQ ID NOs: 8-17 in Table 8) were selected to amplify portionsof HVR1 and HVR2. Additional intelligent primers were designed to mtDNAregions other than HVR1 and HVR2 (SEQ ID NOs: 18-43). The primersdescribed below are generally 10-50 nucleotides in length, 15-35nucleotides in length, or 18-30 nucleotides in length.

TABLE 8 Intelligent Primer Pairs for Analysis of mtDNA Forward ReversePrimer Forward Primer SEQ ID Reverse Primer SEQ ID Pair Name SequenceNO: Sequence NO: HMTHV2_AND TCACGCGATAGCATTGCG 8 TGGTTTGGCAGAGATGTGTTTA9 RSN_76_353_(—) AGT TMOD HMTHV2_AND TCTCACGGGAGCTCTCCATGC 10TCTGTTAAAAGTGCATACCGCC 11 RSN_29_429_(—) A TMOD HMTHV1_ANDTGACTCACCCATCAACAACCGC 12 TGAGGATGGTGGTCIAAGGGAC 13 RSN_16065_(—)16410_TMOD HMTHV1_AND TGACTCACCCATCAACAACCGC 14 TGGATTTGACTGTAATGTGCTA15 RSN_16065_(—) 16354_TMOD HMTHV1_AND TGACTCACCCATCAACAACCGC 16TGAAGGGATTTCACTGTAATGT 17 RSN_16064_(—) GCTATG 16359 HMT_ASN_16GAAGCAGATTTGGGTACCACC 18 GTGTGTGTGCTGGGTAGGATG 19 036_522 HMT_ASN_81TACGGTCAATGCTCTGAAATCT 20 TGGTAAGAAGTGGGCTAGGGCA 21 62_8916 GTGG TTHMT_ASN_12 TTATGTAAAATCCATTGTCGCA 22 TGGTGATAGCGCCTAAGCATAG 23 438_13189TCCACC TG HMT_ASN_14 TCCCATTACTAAACCCACACTC 24 TTTCGTGCAAGAATAGGAGGTG 25629_15353 AACAG GAG HMT_ASN_94 TAAGGCCTTCGATACGGGATAA 26TAGGGTCGAAGCCGCACTCG 27 35_10188 TCCTA HMT_ASN_10 TACTCCAATGCTAAAACTAATC28 TGTGAGGCGTATTATACCATAG 29 753_11500 GTCCCAAC CCG HMT_ASN_15TCCTAGGAATCACCTCCCATTC 30 TAGAATCTTAGCTTTGGGTGCT 31 369_16006 CGAAATGGTG HMT_ASN_13 TGGCAGCCTAGCATTAGCAGGA 32 TGGCTGAACATTGTTTGTTGGT 33461_14206 ATA GT HMT_ASN_34 TCGCTGACGCCATAAAACTCTT 34TAAGTAATGCTAGGGTGAGTGG 35 52_4210 CAC TAGGAAG HMT_ASN_77TAACTAATACTAACATCTCAGA 36 TTTATGGGCTTTGGTGAGGGAG 37 34_8493 CGCTCAGGAGTA HMT_ASN_63 TACTCCCACCCTGGAGCCTC 38 TGCTCCTATTGATAGGACATAG 39 09_7058TGGAAGTG HMT_ASN_76 TTATCACCTTTCATGATCACGC 40 TGGCATTTCACTGTAAAGAGGT 4144_8371 CCT GTTGG HMT_ASN_26 TGTATGAATGGCTCCACGAGGG 42TCGGTAAGCATTAGGAATGCCA 43 26_3377 T TTGC

The process of the analysis is shown in FIG. 19. After amplification byPCR (210), the PCR products were subjected to restriction digests (220)with RsaI for HVR1 and a combination of HpaII, HpyCH4IV, PacI and EaeIfor HVR2 in order to obtain amplicon segments suitable for analysis byFTICR-MS (230). The data were processed to obtain mass data for eachamplicon segment (240) which were then compared to the masses calculatedfor theoretical digests from the FBI mtDNA database by a scoring scheme(250). Digestion pattern matches were scored by the sum of (i) thepercentage of expected complete digest fragments observed, (ii) thepercentage of fragments with a “floating” percentage of potentialincomplete digest fragments (to increase sensitivity for incompletedigestion—these are assigned lower weight), (iii) the percentage of thesequence covered by matched masses, (iv) the number of mass peaksaccounted for in the theoretical database digest, and (v) the weightedscore for matched peaks, weighted by their observed abundance. HVR1 andHVR2 scores were combined and all database entries were sorted by highscore. Even in the absence of an exact match in the database, themajority of entries can be ruled out by observing a much lower matchscore than the maximum score. One with relevant skill in the art willrecognize that development of such scoring procedures is can beaccomplished without undue experimentation.

The results of analysis of sample 1 are shown in FIGS. 20A and 20B. Inthis example, the utility of mass determination of amplicon digestsegments is indicated. In FIG. 20A, predicted and actual mass data withscoring parameters for length heteroplasmy (HV1-1-outer-variants 1 and2) in the digest segment from position 94 to 145(variant 1)/146(variant2) are shown. FIG. 20B indicates that, whereas sequencing fails toresolve the variants due to the length heteroplasmy, mass determinationdetects multiple species simultaneously and indicates abundance ratios.In this case, the ratio of variant 1 to variant 2 (short to longalleles) is 1:3. Thus, in addition to efficiency of characterization ofindividual digested amplicon fragments, the relative abundances ofheteroplasmic variants can be determined.

Of the 10 samples analyzed by the present methods, 9 samples wereverified as being consistent with members of the FBI database. Theremaining sample could not be analyzed due to a failure of PCR toproduce an amplification product.

Various modifications of the invention, in addition to those describedherein, will be apparent to those skilled in the art from the foregoingdescription. Such modifications are also intended to fall within thescope of the appended claims. Each reference cited in the presentapplication is incorporated herein by reference in its entirety

1.-28. (canceled)
 29. A method of identifying a nucleic acid sequencefrom a human sample, comprising: a) contacting nucleic acid from a humansample with two or more oligonucleotide primers that hybridize tosequence regions of said nucleic acid that are conserved among differentbioagents, wherein said conserved sequence regions flank a variablesequence region to produce an amplification product; b) determining thebase composition of said amplification product; and c) identifying saidnucleic acid sequence from a human sample by comparing said determinedbase composition to a database of base compositions from a plurality ofdifferent bioagents.
 30. The method of claim 29, wherein said bioagentis selected from the group of bioagents consisting of a viral bioagent,a bacterial bioagent, a fungal bioagent, a protozoal bioagent, aparasitic bioagent, a mammalian bioagent, and a human bioagent.
 31. Themethod of claim 29, wherein said bioagent is selected from the group ofbioagents consisting of an evolving bioagent, a mutating bioagent, arecombinant bioagent, a replicating bioagent, a living bioagent, a deadbioagent, and an engineered bioagent.
 32. The method of claim 29,wherein said bioagent is not previously known to exist.
 33. The methodof claim 29, wherein said human sample is selected from the groupconsisting of a body fluid sample, a urine sample, a blood sample, aserum sample, a plasma sample, a spinal fluid sample, a sputum sample, abile sample, a stool sample, a saliva sample, a tear sample, a mucussample, a gastric content sample, a sweat sample, an exocrine glandsample, an endocrine gland sample, a pus sample, a wound swab sample, aculture swab sample, a surgical sample, a tissue sample, a biopsysample, a brush sample, a culture media sample, a forensic sample, abody surface sample, a skin sample, a mucus membrane sample, a hairsample, a nail sample, a cosmetic sample, a clothing sample, a beddingsample, an environmental sample, a stored sample, a preserved sample, aformalin sample, a paraffin sample, an immunohistochemistry sample, ahistology sample, a living sample, and a post-mortem sample.
 34. Themethod of claim 29, wherein said human sample comprises at least twobioagents of different genus, and wherein said nucleic acid from saidsample is contacted with two or more oligonucleotide primers configuredto identify two or more bioagents of different genus.
 35. The method ofclaim 29, wherein said human sample comprises at least two bioagents ofdifferent species, and wherein said nucleic acid from said sample iscontacted with two or more oligonucleotide primers configured toidentify two or more bioagents of different species.
 36. The method ofclaim 29, further comprising purifying said nucleic acid prior toproduction of said amplification product.
 37. The method of claim 29,further comprising modifying said nucleic acid prior to production ofsaid amplification product.
 38. The method of claim 29, wherein saidnucleic acid is selected from the group consisting of genomic DNA, RNA,DNA that is complementary to RNA, DNA that is synthesized from RNA,double-stranded DNA, single stranded DNA, DNA that is the product ofamplification, DNA that is fragmented, nuclear DNA, mitochondrial DNA,cytoplasmic DNA and extracellular DNA.
 39. The method of claim 29,wherein said two or more oligonucleotide primers are about 15-35nucleobases in length, and wherein said two or more oligonucleotideprimers comprise at least 70%, at least 80%, at least 90%, at least 95%,or at least 100% sequence identify with said conserved sequence regions.40. The method of claim 29, wherein said amplification product is 45 to200 nucleobases in length.
 41. The method of claim 29, wherein anon-templated T residue on the 5′-end of at least one of said two ormore oligonucleotide primers is removed.
 42. The method of claim 29,wherein at least one of said two or more oligonucleotide primerscomprises a non-templated T residue on the 5′-end.
 43. The method ofclaim 29, wherein at least one of said two or more oligonucleotideprimers comprises at least one molecular mass modifying tag.
 44. Themethod of claim 29, wherein at least one of said two or moreoligonucleotide primers comprises at least one modified nucleobase. 45.The method of claim 44, wherein said modified nucleobase is5-propynyluracil or 5-propynylcytosine.
 46. The method of claim 44,wherein said modified nucleobase is a mass modified nucleobase.
 47. Themethod of claim 46, wherein said mass modified nucleobase is 5-Iodo-C.48. The method of claim 44, wherein said modified nucleobase is auniversal nucleobase.
 49. The method of claim 48, wherein said universalnucleobase is inosine.
 50. The method of claim 29, wherein said bioagentis identified at the genus, species, sub-species, strain, sub-type ornucleotide polymorphism levels.
 51. The method of claim 29, wherein saidtwo or more oligonucleotide primers comprise multiple oligonucleotideprimer sets configured for identification of diverse bioagents.
 52. Themethod of claim 29, wherein said conserved sequence regions are within agene.
 53. The method of claim 29, wherein said conserved sequenceregions are within a coding region of a gene.
 54. The method of claim29, wherein said conserved sequence regions are within a regulatoryregion of a gene.
 55. The method of claim 29, wherein said variablesequence region is within a gene.
 56. The method of claim 29, whereinsaid variable sequence region is within a coding region of a gene. 57.The method of claim 29, wherein said variable sequence region is withina regulatory region of a gene.
 58. The method of claim 29, wherein saidconserved sequence regions are about 10 to 100 nucleobases in length.59. The method of claim 29, wherein said variable sequence region isabout 10 to 200 nucleobases in length.
 60. The method of claim 29,wherein said amplification product is produced by polymerase chainreaction.
 61. The method of claim 29, further comprising purifying saidamplification product.
 62. The method of claim 29, wherein said basecomposition is determined by mass spectrometry.
 63. The method of claim62, wherein said mass spectrometry is ESI mass spectrometry.
 64. Themethod of claim 29, wherein said base composition of said amplificationproduct comprises identification of the number of A residues, Cresidues, T residues, G residues, U residues, analogs thereof and/ormass tag residues thereof in said amplification product.
 65. The methodof claim 29, wherein said base composition is determined withoutsequencing said amplification product.
 66. The method of claim 29,wherein said comparing comprises identifying a match between saiddetermined base composition and at least one entry within said databaseof base compositions from a plurality of different bioagents.
 67. Themethod of claim 29, wherein said identifying said bioagent requires twoor more oligonucleotide primer pairs.
 68. The method of claim 29,wherein said database of base compositions from a plurality of differentbioagents comprises base compositions of genus specific amplificationproducts, family specific amplification products, species specificamplification products, strain specific amplification products, sub-typespecific amplification products, or nucleotide polymorphism specificamplification products produced with said two or more oligonucleotideprimers, wherein one or more matches between said determined basecomposition of said amplification product and one or more entries insaid database identifies said bioagent, classifies a majorclassification of said bioagent, or differentiates between subgroups ofknown and unknown bioagents.
 69. The method of claim 29, wherein saiddatabase of base compositions comprises base composition information forat least 3 different bioagents.
 70. The method of claim 29, wherein saiddatabase of base compositions comprises base composition information forat least 4 different bioagents.
 71. The method of claim 29, wherein saiddatabase of base compositions comprises base composition information forat least 8 different bioagents.
 72. The method of claim 29, wherein saiddatabase of base compositions comprises base composition information forat least 19 different bioagents.
 73. The method of claim 29, whereinsaid database of base compositions comprises base compositioninformation for at least 30 different bioagents.
 74. The method of claim29, wherein said database of base compositions comprises at least 12unique base compositions.
 75. The method of claim 29, wherein saiddatabase of base compositions comprises at least 40 unique basecompositions.
 76. The method of claim 29, wherein said database of basecompositions comprises base composition information for a bioagent fromtwo or more genuses selected from the group consisting of Acinetobacter,Aeromonas, Bacillus, Bacteroides, Bartonella, Bordetella, Borrelia,Brucella, Burkholderia, Campylobacter, Chlamydia, Chlamydophila,Clostridium, Coxiella, Enterococcus, Escherichia, Francisella,Fusobacterium, Haemophilus, Helicobacter, Klebsiella, Legionella,Leptospira, Listeria, Moraxella, Mycobacterium, Mycoplasma, Neisseria,Proteus, Pseudomonas, Rhodobacter, Rickettsia, Salmonella, Shigella,Staphylococcus, Streptobacillus, Streptomyces, Treponema, Ureaplasma,Vibrio, or Yersinia.
 77. The method of claim 29, wherein said databaseof base compositions comprises base composition information for abioagent from each of the genuses of Acinetobacter, Aeromonas, Bacillus,Bacteroides, Bartonella, Bordetella, Borrelia, Brucella, Burkholderia,Campylobacter, Chlamydia, Chlamydophila, Clostridium, Coxiella,Enterococcus, Escherichia, Francisella, Fusobacterium, Haemophilus,Helicobacter, Klebsiella, Legionella, Leptospira, Listeria, Moraxella,Mycobacterium, Mycoplasma, Neisseria, Proteus, Pseudomonas, Rhodobacter,Rickettsia, Salmonella, Shigella, Staphylococcus, Streptobacillus,Streptomyces, Treponema, Ureaplasma, Vibrio, or Yersinia.
 78. The methodof claim 29, wherein said database of base compositions comprises basecomposition information for a bioagent from two or more orders orfamilies selected from the group consisting of Smallpox virus,Arenavirus, Bunyaviruses, Mononegavirales, Picornaviruses, Astroviruses,Calciviruses, Nidovirales, Flaviviruses, and Togaviruses.
 79. The methodof claim 29, wherein said database of base compositions comprises basecomposition information for a bioagent from each of the orders orfamilies of Smallpox virus, Arenavirus, Bunyaviruses, Mononegavirales,Picornaviruses, Astroviruses, Calciviruses, Nidovirales, Flaviviruses,and Togaviruses.
 80. The method of claim 29, wherein said basecompositions in said database are associated with bioagent identity. 81.The method of claim 29, wherein said base compositions in said databaseare associated with bioagent geographic origin.
 82. The method of claim29, wherein said comparing step is performed by a computer.
 83. Themethod of claim 82, wherein said computer identifies a match betweensaid determined base composition of said amplification product and oneor more entries in database of base compositions from a plurality ofdifferent bioagents with a probability algorithm.
 84. The method ofclaim 29, wherein said database is stored on a computer.
 85. The methodof claim 84, wherein said computer is a local computer.
 86. The methodof claim 84, wherein said computer is a remote computer.
 87. The methodof claim 29, wherein said identifying a nucleic acid sequence from ahuman sample comprises interrogation of said database with two or moredifferent base compositions associated with said plurality of bioagents.88. The method of claim 29, wherein said database of base compositionscomprises at least 10 base compositions.
 89. The method of claim 29,wherein said database of base compositions comprises at least 20 basecompositions.
 90. The method of claim 29, wherein said database of basecompositions comprises at least 30 base compositions.
 91. The method ofclaim 29, wherein said database of base compositions comprises at least40 base compositions.
 92. The method of claim 29, wherein said databaseof base compositions comprises at least 50 base compositions.
 93. Themethod of claim 29, wherein said database of base compositions comprisesat least 60 base compositions.
 94. The method of claim 29, wherein saiddatabase of base compositions comprises at least 70 base compositions.95. The method of claim 29, wherein said database of base compositionscomprises at least 80 base compositions.
 96. The method of claim 29,wherein said database of base compositions comprises at least 90 basecompositions.
 97. The method of claim 29, wherein said database of basecompositions comprises at least 100 base compositions.
 98. The method ofclaim 29, wherein said database of base compositions comprises at least500 base compositions.
 99. The method of claim 29, wherein said databaseof base compositions comprises at least 1000 base compositions.
 100. Themethod of claim 29, wherein said two or more oligonucleotide primershybridize to sequence regions of human nucleic acid.
 101. The method ofclaim 29, wherein said human sample comprises human nucleic acid andnucleic acid from a bioagent wherein said bioagent is selected from thegroup consisting of a viral bioagent, a bacterial bioagent, a fungalbioagent, a protozoal bioagent, a parasitic bioagent, and a mammalianbioagent.
 102. A system, comprising: a) a nucleic acid amplificationcomponent; b) a base composition determination component; and c) a basecomposition identification component comprising a database of basecompositions from a plurality of bioagents wherein said bioagentscomprise human bioagents.
 103. The system of claim 102, furthercomprising a nucleic acid purification component.
 104. The system ofclaim 103, wherein said nucleic acid purification component comprisesone or more buffer manipulations, one or more salt manipulations, one ormore thermal manipulations, one or more pH manipulations, one or moremechanical manipulations, one or more centrifugation manipulations, orone or more magnetic manipulations.
 105. The system of claim 102,wherein said nucleic acid amplification component comprises athermocycler.
 106. The system of claim 102, wherein said nucleic acidamplification component comprises one or more salts, one or morebuffers, one or more purified oligonucleotide primers, one or moredNTPs, or one or more enzymes.
 107. The system of claim 102, whereinsaid base composition identification component comprises a massspectrometer.
 108. The system of claim 107, wherein said massspectrometer is an ESI mass spectrometer.
 109. The system of claim 102,wherein said base composition identification component comprises aprocessor.
 110. The system of claim 109, further comprising a computerprogram on a computer readable medium configured to direct saidprocessor to coordinate the operation of said nucleic acid component,said base composition determination component, and said base compositionidentification component.
 111. The system of claim 109, wherein saidprocessor is configured to process mass spectrometry data to basecomposition data.
 112. The system of claim 109, wherein said processoris configured to process base composition date to identify a bioagent.113. The system of claim 102, wherein said database of base compositionscomprises at least 10 base compositions.
 114. The system of claim 102,wherein said database of base compositions comprises at least 20 basecompositions.
 115. The system of claim 102, wherein said database ofbase compositions comprises at least 30 base compositions.
 116. Thesystem of claim 102, wherein said database of base compositionscomprises at least 40 base compositions.
 117. The system of claim 102,wherein said database of base compositions comprises at least 50 basecompositions.
 118. The system of claim 102, wherein said database ofbase compositions comprises at least 60 base compositions.
 119. Thesystem of claim 102, wherein said database of base compositionscomprises at least 70 base compositions.
 120. The system of claim 102,wherein said database of base compositions comprises at least 80 basecompositions.
 121. The system of claim 102, wherein said database ofbase compositions comprises at least 90 base compositions.
 122. Thesystem of claim 102, wherein said database of base compositionscomprises at least 100 base compositions.
 123. The system of claim 102,wherein said database of base compositions comprises at least 500 basecompositions.
 124. The system of claim 102, wherein said database ofbase compositions comprises at least 1000 base compositions.
 125. Thesystem of claim 102, wherein said plurality of bioagents comprisesbioagents that differ by genus, species, sub-species, strain, sub-typeor nucleotide polymorphism.
 126. The system of claim 102, wherein saidplurality of bioagents comprises one or more viral bioagents, one ormore bacterial bioagents, one or more fungal bioagents, one or moreprotozoal bioagents, one or more parasitic bioagents, one or moremammalian bioagents, or one or more human bioagents.